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	<title>丕子 &#187; CBIR</title>
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		<title>搜狗互联网图片库2.0（SogouP2.0）正式发布</title>
		<link>http://www.zhizhihu.com/html/y2011/3350.html</link>
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		<pubDate>Thu, 01 Sep 2011 08:50:59 +0000</pubDate>
		<dc:creator>丕子</dc:creator>
				<category><![CDATA[科研]]></category>
		<category><![CDATA[CBIR]]></category>
		<category><![CDATA[互联网图片库]]></category>
		<category><![CDATA[图像]]></category>
		<category><![CDATA[图像标注]]></category>
		<category><![CDATA[图像检索]]></category>
		<category><![CDATA[搜狗实验室]]></category>

		<guid isPermaLink="false">http://www.zhizhihu.com/?p=3350</guid>
		<description><![CDATA[@搜狗实验室：搜狗互联网图片库2.0（SogouP2.0）正式发布： 1000万张图片，200万组图片源，2T数据规模，包括原图文件、URL、所在网页的URL、所在网页中的Surrounding Text文本、同主题系列图片等信息。图片库还包括了一个识图搜索结果人工标注集合，用于训练和评测。http://www.sogou.com/labs/dl/p2.html。现在开始接受在线申请。 记得很久很久之前搜狗实验室就不断的发布数据集供大家申请使用，真是赞。 这次的图像库的内容：收集了包括人物、动物、建筑、机械、风景、运动等类别，总数高达1000万张图片。对于每张图片，搜狗给出了图片的原图文件、图片的URL、 图片所在网页的URL、图片所在网页中的Surrounding Text文本、同主题系列图片等信息。图片库还包括了一个识图搜索结果人工标注集合，用于训练和评测。 另外注意下搜狗的图片搜索http://pic.sogou.com/已经发布了CBIR的应用，就是用图来找图。搜索框里有了相机icon了。还不错，挺准的。 好东西啊，感谢搜狗。 &#160; 相关文章搜狗竟然也有了基于内容图像检索应用 (3)再收集一下基于内容图像检索系统 (7)最近图像检索应用的新闻 (0)图像检索垂直应用热了？-淘宝图想 (21)介绍一家新公司：淘淘搜(搜图购) (11)[搜索]5个黑白图像搜索引擎 (14)Google Image Swirl-聚类多样性的CBIR (24)Tamura纹理特征的原理以及matlab源码 (12)CBIR: Texture Features (0)Gray-level Co-occurrence Matrix(灰度共生矩阵) (1)<table class="wumii-related-items" cellspacing="0" cellpadding="3" border="0"  style="clear: both;">
    
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			<content:encoded><![CDATA[<p><a href="http://weibo.com/2335069057" target="_blank">@搜狗实验室</a>：搜狗互联网图片库2.0（SogouP2.0）正式发布： 1000万张图片，200万组图片源，2T数据规模，包括原图文件、URL、所在网页的URL、所在网页中的Surrounding Text文本、同主题系列图片等信息。图片库还包括了一个识图搜索结果人工标注集合，用于训练和评测。<a href="http://www.sogou.com/labs/dl/p2.html" target="_blank">http://www.sogou.com/labs/dl/p2.html</a>。现在开始接受在线申请。</p>
<p>记得很久很久之前搜狗实验室就不断的发布数据集供大家申请使用，真是赞。</p>
<p><img class="aligncenter" src="http://www.sogou.com/labs/images/banner.jpg" alt="http://www.sogou.com/labs/images/banner.jpg" width="559" height="112" /></p>
<p>这次的图像库的内容：收集了包括人物、动物、建筑、机械、风景、运动等类别，总数高达1000万张图片。对于每张图片，搜狗给出了图片的原图文件、图片的URL、 图片所在网页的URL、图片所在网页中的Surrounding Text文本、同主题系列图片等信息。图片库还包括了一个识图搜索结果人工标注集合，用于训练和评测。</p>
<p>另外注意下搜狗的图片搜索http://pic.sogou.com/已经发布了CBIR的应用，就是用图来找图。搜索框里有了相机icon了。还不错，挺准的。</p>
<p>好东西啊，感谢搜狗。</p>
<p>&nbsp;</p>
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		<slash:comments>4</slash:comments>
		</item>
		<item>
		<title>搜狗竟然也有了基于内容图像检索应用</title>
		<link>http://www.zhizhihu.com/html/y2011/3291.html</link>
		<comments>http://www.zhizhihu.com/html/y2011/3291.html#comments</comments>
		<pubDate>Tue, 16 Aug 2011 13:29:07 +0000</pubDate>
		<dc:creator>丕子</dc:creator>
				<category><![CDATA[技术]]></category>
		<category><![CDATA[科研]]></category>
		<category><![CDATA[CBIR]]></category>
		<category><![CDATA[以图搜图]]></category>
		<category><![CDATA[图像检索]]></category>
		<category><![CDATA[基于内容图像检索]]></category>
		<category><![CDATA[搜狗]]></category>

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		<description><![CDATA[今天忽然发现搜狗的图像检索框中也有了和谷歌似的小相机图标，竟然也做起了CBIR（基于内容图像检索），我体验了一下，结果还算是不错。 其实基于互联网的CBIR来说，只要克服了效率问题，感觉找到TOP n幅相似的图像很容易的，因为一个假设就是互联网中已经有很很多很多到查询图像距离为0的图像，只要距离为0的图像足够多，那么结果好就不足为奇了，这是原因之一。当然还有特征描述以及距离度量等原因。 另外，搜狗貌似要开放数据集：@茹立云：搜狗实验室即将开放一批识图数据：包括类似图片、图片surrounding text，图片同主题图片及surrounding text，图片查询点击文本等；为识图研究提供更好的语料支持。 -----------------来自: 新浪科技的新闻------------ 搜狗识图搜索功能 8月16日晚间消息，搜狗图片搜索( http://pic.sogou.com/)于今年8月15日正式推出了具备以图搜图功能的新产品——识图搜索。 识图搜索能实现以图搜图，即通过上传图片、鼠标拖拽、鼠标选图、输入图片URL地址等多种方式搜索，找到互联网上与这张图片相似的其他图片，并且利用图片识别技术，进一步分析图片内容的主题，找到与这张图片同主题的其他图片。 根据搜狐公布的第二季度财报，搜狗业务第二季度收入达1360万美元，较去年同期增长252%，较上一季度增长71%。 相关文章再收集一下基于内容图像检索系统 (7)搜狗互联网图片库2.0（SogouP2.0）正式发布 (4)最近图像检索应用的新闻 (0)图像检索垂直应用热了？-淘宝图想 (21)介绍一家新公司：淘淘搜(搜图购) (11)[搜索]5个黑白图像搜索引擎 (14)Google Image Swirl-聚类多样性的CBIR (24)Tamura纹理特征的原理以及matlab源码 (12)CBIR: Texture Features (0)Gray-level Co-occurrence Matrix(灰度共生矩阵) (1)<table class="wumii-related-items" cellspacing="0" cellpadding="3" border="0"  style="clear: both;">
    
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			<content:encoded><![CDATA[<p>今天忽然发现搜狗的图像检索框中也有了和谷歌似的小相机图标，竟然也做起了CBIR（基于内容图像检索），我体验了一下，结果还算是不错。</p>
<p>其实基于互联网的CBIR来说，只要克服了效率问题，感觉找到TOP n幅相似的图像很容易的，因为一个假设就是互联网中已经有很很多很多到查询图像距离为0的图像，只要距离为0的图像足够多，那么结果好就不足为奇了，这是原因之一。当然还有特征描述以及距离度量等原因。</p>
<p>另外，搜狗貌似要开放数据集：<a href="http://weibo.com/ruliyun">@茹立云<img title="新浪个人认证" src="http://img.t.sinajs.cn/t35/style/images/common/transparent.gif" alt="" /></a>：搜狗实验室即将开放一批识图数据：包括类似图片、图片surrounding text，图片同主题图片及surrounding text，图片查询点击文本等；为识图研究提供更好的语料支持。</p>
<p>-----------------来自: <a id="link_source2" href="http://tech.sina.com.cn/i/2011-08-16/19015937244.shtml" target="_blank">新浪科技</a>的新闻------------</p>
<p><img class="aligncenter" src="http://pic003.cnblogs.com/2011/157064/201108/2011081620012395.jpg" alt="" /></p>
<p>搜狗识图搜索功能</p>
<p>8月16日晚间消息，搜狗图片搜索( http://pic.sogou.com/)于今年8月15日正式推出了具备以图搜图功能的新产品——识图搜索。</p>
<p>识图搜索能实现以图搜图，即通过上传图片、鼠标拖拽、鼠标选图、输入图片URL地址等多种方式搜索，找到互联网上与这张图片相似的其他图片，并且利用图片识别技术，进一步分析图片内容的主题，找到与这张图片同主题的其他图片。</p>
<p>根据搜狐公布的第二季度财报，搜狗业务第二季度收入达1360万美元，较去年同期增长252%，较上一季度增长71%。</p>
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		</item>
		<item>
		<title>再收集一下基于内容图像检索系统</title>
		<link>http://www.zhizhihu.com/html/y2011/2737.html</link>
		<comments>http://www.zhizhihu.com/html/y2011/2737.html#comments</comments>
		<pubDate>Sun, 06 Mar 2011 13:42:34 +0000</pubDate>
		<dc:creator>丕子</dc:creator>
				<category><![CDATA[技术]]></category>
		<category><![CDATA[科研]]></category>
		<category><![CDATA[CBIR]]></category>
		<category><![CDATA[图像检索]]></category>
		<category><![CDATA[基于内容图像检索]]></category>
		<category><![CDATA[机器学习]]></category>
		<category><![CDATA[电子商务]]></category>
		<category><![CDATA[计算机视觉]]></category>

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		<description><![CDATA[基于内容图像检索已经发展二十多年，基本简单技术已经成熟，总结一下几个系统。 下面的十款搜索引擎可以帮你实现，以图找图，以图搜图，以图片搜索相似的图片。 一：http://tineye.com/ Tineye是典型的以图找图搜索引擎，输入本地硬盘上的图片或者输入图片网址，即可自动帮你搜索相似图片，搜索准确度相对来说还比较令人满意。 TinEye是加拿大Idée公司研发的相似图片搜索引擎，TinEye主要用途有：1、发现图片的来源与相关信息；2、研究追踪图片信息在互联网的传播；3、找到高分辨率版本的图片；4、找到有你照片的网页；5、看看这张图片有哪些不同版本。 二：http://shitu.baidu.com 百度正式上线了其最新的搜索功能——“识图”（shitu.baidu.com）。该功能是百度基于相似图片识别技术，让用户通过上传本地图片 或者输入图片的URL地址之后，百度再根据图像特征进行分析，进而从互联网中搜索出与此相似的图片资源及信息内容。但需要注意的是，用户上传本地图片时， 图片的文件要小于5M，格式可为JPG、JPEG、GIF、PNG、BMP等图片文件。 三：http://www.gazopa.com/ GazoPa搜索图片时，不依据关键词进行检索，而是通过图片自身的某些特征（例如色彩，形状等信息）来进行搜索。GazoPa搜索方式有四种： 第一种是传统的通过关键词搜索图片，但在传统图片搜索领域GazoPa与google等搜索引擎无法竞争。 第二种是创新的通过图片搜索图片，但在此领域GazoPa无法与TinEye相竞争。TinEye很容易就能搜索出与原图最接近的一些结果，而GazoPa很多时候的搜索结果则完全无法与原图匹配。 第三种是通过手绘图片搜索图片，这种方式其实没太大用处。GazoPa虽然有这样那样的不足之处，但也算是一个很有独创性的搜索引擎。GazoPa目前还处在内测阶段，想要加入测试的可以在官网上留下你的邮箱地址，收到邀请后你就可以测试使用了。 第四种是通过视频缩略图搜索视频，GazoPa仅凭一张视频缩略图就可找到相关视频。只要有截图，就可以找到截图的视频！ 四、http://similar-images.googlelabs.com/ Google实验室的图片搜索：输入一个关键词后，例如“lake”，返回的页面里面点击某个图片的下面的Similar images，运用Google 类似图片搜索功能引擎，即刻为你把类似的图片全部搜索出来，展示给用户以便查看。其准确率、相似率相对比较高。 五、http://www.picitup.com/ Picitup是一个刚开始公测的专业图片搜索引擎，功能非常强大，并支持中文关键字的搜索，是国内图片爱好者的不错选择。Picitup主要 支持关键字的搜索，但在它的特色搜索项目——名人匹配搜索（Celebritymatchup）中，你可以通过上传本地照片来进行搜索，不过结果一般让人 失望。Picitup可以通过在搜索结果页选择过滤方式来筛选图片，比如可以按颜色、头像（人脸）、风景、产品四种类别来过滤搜索结果。 Picitup最大特点是提供相似图片搜索，即通过关键字找到初始图片，点击初始图片下面的similar pictures按钮，即可搜索与该张图片类似的图片。其实质和Google实验室类似图片搜索是一样的。 六、http://www.tiltomo.com/ Tiltomo是由 Flickr 开发的一个搜索工具，主要用来维护Flickr 自己的图片数据库，其搜索算法主要是基于相似的主题风格或相似的色调和材质。 七、http://cn.bing.com/ Live.com允许你进行一次关键字搜索后再执行相似性的搜索。你可以为Live索引中的任意一张图片寻找相似的图片，但搜索结果看起来并不是很精确。 八、http://www.xcavator.net Xcavator 和Live.com很相似，你需要先输入一个关键字，然后在搜索结果中挑选一张图片，在根据这张图片的特点来进行搜索。 九、http://www.incogna.com Incogna的搜索速度非常快，主要是基于色彩和形状上的相似性。 十、http://www.terragalleria.com Terragalleria主要基于视觉上的相似性，而不考虑图片的内容。 十一、http://labs.ideeinc.com/upload/ Byo image search是根据你上传的图片来搜索相似的图片，算法主要是基于色彩，也包括主题风格。 十二、淘淘搜：http://www.taotaosou.com/ CBIR在电子商务的典型应用。 十三、淘宝图像：http://imagine.taobao.com 是淘淘搜的团队做的。结果更加绚丽实用。 来自: www.u148.net 相关文章搜狗竟然也有了基于内容图像检索应用 (3)人的视觉和计算机的视觉 (14)介绍一家新公司：淘淘搜(搜图购) (11)[搜索]5个黑白图像搜索引擎 (14)People Counting [...]<table class="wumii-related-items" cellspacing="0" cellpadding="3" border="0"  style="clear: both;">
    
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			<content:encoded><![CDATA[<p>基于内容图像检索已经发展二十多年，基本简单技术已经成熟，总结一下几个系统。</p>
<p><img class="aligncenter" src="http://gdimitriou.eu/wp-content/uploads/2008/04/google-image-search.jpg" alt="http://gdimitriou.eu/wp-content/uploads/2008/04/google-image-search.jpg" /></p>
<p>下面的十款搜索引擎可以帮你实现，以图找图，以图搜图，以图片搜索相似的图片。</p>
<p>一：<a href="http://tineye.com/" target="_blank">http://tineye.com/</a></p>
<p>Tineye是典型的以图找图搜索引擎，输入本地硬盘上的图片或者输入图片网址，即可自动帮你搜索相似图片，搜索准确度相对来说还比较令人满意。</p>
<p>TinEye是加拿大Idée公司研发的相似图片搜索引擎，TinEye主要用途有：1、发现图片的来源与相关信息；2、研究追踪图片信息在互联网的传播；3、找到高分辨率版本的图片；4、找到有你照片的网页；5、看看这张图片有哪些不同版本。</p>
<p>二：<a href="http://shitu.baidu.com/" target="_blank">http://shitu.baidu.com</a></p>
<p>百度正式上线了其最新的搜索功能——“识图”（shitu.baidu.com）。该功能是百度基于相似图片识别技术，让用户通过上传本地图片 或者输入图片的URL地址之后，百度再根据图像特征进行分析，进而从互联网中搜索出与此相似的图片资源及信息内容。但需要注意的是，用户上传本地图片时， 图片的文件要小于5M，格式可为JPG、JPEG、GIF、PNG、BMP等图片文件。</p>
<p>三：<a href="http://www.gazopa.com/" target="_blank">http://www.gazopa.com/</a></p>
<p>GazoPa搜索图片时，不依据关键词进行检索，而是通过图片自身的某些特征（例如色彩，形状等信息）来进行搜索。GazoPa搜索方式有四种：</p>
<p>第一种是传统的通过关键词搜索图片，但在传统图片搜索领域GazoPa与google等搜索引擎无法竞争。</p>
<p>第二种是创新的通过图片搜索图片，但在此领域GazoPa无法与TinEye相竞争。TinEye很容易就能搜索出与原图最接近的一些结果，而GazoPa很多时候的搜索结果则完全无法与原图匹配。</p>
<p>第三种是通过手绘图片搜索图片，这种方式其实没太大用处。GazoPa虽然有这样那样的不足之处，但也算是一个很有独创性的搜索引擎。GazoPa目前还处在内测阶段，想要加入测试的可以在官网上留下你的邮箱地址，收到邀请后你就可以测试使用了。</p>
<p>第四种是通过视频缩略图搜索视频，GazoPa仅凭一张视频缩略图就可找到相关视频。只要有截图，就可以找到截图的视频！</p>
<p>四、<a href="http://similar-images.googlelabs.com/" target="_blank">http://similar-images.googlelabs.com/</a></p>
<p>Google实验室的图片搜索：输入一个关键词后，例如“lake”，返回的页面里面点击某个图片的下面的Similar images，运用Google 类似图片搜索功能引擎，即刻为你把类似的图片全部搜索出来，展示给用户以便查看。其准确率、相似率相对比较高。</p>
<p>五、<a href="http://www.picitup.com/" target="_blank">http://www.picitup.com/</a></p>
<p>Picitup是一个刚开始公测的专业图片搜索引擎，功能非常强大，并支持中文关键字的搜索，是国内图片爱好者的不错选择。Picitup主要 支持关键字的搜索，但在它的特色搜索项目——名人匹配搜索（Celebritymatchup）中，你可以通过上传本地照片来进行搜索，不过结果一般让人 失望。Picitup可以通过在搜索结果页选择过滤方式来筛选图片，比如可以按颜色、头像（人脸）、风景、产品四种类别来过滤搜索结果。</p>
<p>Picitup最大特点是提供相似图片搜索，即通过关键字找到初始图片，点击初始图片下面的similar pictures按钮，即可搜索与该张图片类似的图片。其实质和Google实验室类似图片搜索是一样的。</p>
<p>六、<a href="http://www.tiltomo.com/" target="_blank">http://www.tiltomo.com/</a></p>
<p>Tiltomo是由 Flickr 开发的一个搜索工具，主要用来维护Flickr 自己的图片数据库，其搜索算法主要是基于相似的主题风格或相似的色调和材质。</p>
<p>七、<a href="http://cn.bing.com/" target="_blank">http://cn.bing.com/</a></p>
<p>Live.com允许你进行一次关键字搜索后再执行相似性的搜索。你可以为Live索引中的任意一张图片寻找相似的图片，但搜索结果看起来并不是很精确。<br />
八、<a href="http://www.xcavator.net/" target="_blank">http://www.xcavator.net</a></p>
<p>Xcavator 和Live.com很相似，你需要先输入一个关键字，然后在搜索结果中挑选一张图片，在根据这张图片的特点来进行搜索。</p>
<p>九、<a href="http://www.incogna.com/" target="_blank">http://www.incogna.com</a></p>
<p>Incogna的搜索速度非常快，主要是基于色彩和形状上的相似性。</p>
<p>十、<a href="http://www.terragalleria.com/" target="_blank">http://www.terragalleria.com</a></p>
<p>Terragalleria主要基于视觉上的相似性，而不考虑图片的内容。</p>
<p>十一、<a href="http://labs.ideeinc.com/upload/" target="_blank">http://labs.ideeinc.com/upload/</a><br />
Byo image search是根据你上传的图片来搜索相似的图片，算法主要是基于色彩，也包括主题风格。</p>
<p>十二、淘淘搜：<a href="http://www.taotaosou.com/" target="_blank">http://www.taotaosou.com/</a></p>
<p>CBIR在电子商务的典型应用。</p>
<p><img class="aligncenter" src="http://www.taotaosou.com/img/index_logo.png" alt="http://www.taotaosou.com/img/index_logo.png" /></p>
<p>十三、淘宝图像：<a href="http://imagine.taobao.com/imagine/index.htm" target="_blank">http://imagine.taobao.com</a></p>
<p>是淘淘搜的团队做的。结果更加绚丽实用。</p>
<p>来自: <a id="link_source2" href="http://www.u148.net/article/33760.html" target="_blank">www.u148.net</a></p>
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		<slash:comments>7</slash:comments>
		</item>
		<item>
		<title>最近图像检索应用的新闻</title>
		<link>http://www.zhizhihu.com/html/y2011/2605.html</link>
		<comments>http://www.zhizhihu.com/html/y2011/2605.html#comments</comments>
		<pubDate>Fri, 11 Feb 2011 13:54:54 +0000</pubDate>
		<dc:creator>丕子</dc:creator>
				<category><![CDATA[技术]]></category>
		<category><![CDATA[CBIR]]></category>
		<category><![CDATA[图像检索]]></category>
		<category><![CDATA[机器视觉]]></category>

		<guid isPermaLink="false">http://一个是谷歌的：谷歌将推出一款名为GoogleShopper的iPhone应用，配备语音、图像和本地化搜索功能。谷歌去年曾面向Android平台推出过这款应用，可以根据文本、语音和条形码寻找产品，并进行价格对比。如果搜索“惠普打印机”，便可以获得一系列不同型号的打印机，以及附近的商户列表。谷歌还会根据用户评论显示各个产品的评级。当用户选定具体某个项目后，GoogleShopper会显示商品的详细信息，用户可以查看售卖相关产品的网上商家或本地商家；一旦用户选择了本地商家，程序将显</guid>
		<description><![CDATA[一个是谷歌的： 谷歌将推出一款名为Google Shopper的iPhone应用，配备语音、图像和本地化搜索功能。 谷歌去年曾面向Android平台推出过这款应用，可以根据文本、语音和条形码寻找产品，并进行价格对比。如果搜索“惠普打印机”，便可以获得一系列不同型号的打印机，以及附近的商户列表。谷歌还会根据用户评论显示各个产品的评级。 当用户选定具体某个项目后，Google Shopper会显示商品的详细信息，用户可以查看售卖相关产品的网上商家或本地商家；一旦用户选择了本地商家，程序将显示各家店铺的存货情况。用户可以 “标记”某个商品，并通过Facebook、Twitter或Google Reader和朋友分享。 和Android版本一样，iPhone版的Shopper速度快、易上手、效率高。不管用户身在何处，程序都可以提供可靠的价格比较。Google Shopper目前已经对ShopSaxy等购物和条形码识别应用产生了威胁。 目前Google Shopper已经登录苹果程序应用商店，系统版本在iOS 4或以上的iPhone可以使用。 再一个是微软的： 微软刚刚宣布了Bing图像搜索去年发布以来的第一次重大更新，实际上微软一直在为图像搜索引擎更新搜索算法和提供共享搜索结果的功能，但这次的功 能改进却直接和用户体验相关，利用标签形式列举的相关关键词可以带来更多具有相关性的图像，并且还更新了布局，可以通过网格的形式确定搜索结果的尺寸。 相关文章Google Image Swirl-聚类多样性的CBIR (24)搜狗互联网图片库2.0（SogouP2.0）正式发布 (4)搜狗竟然也有了基于内容图像检索应用 (3)再收集一下基于内容图像检索系统 (7)图像检索垂直应用热了？-淘宝图想 (21)百度竟然推出图像相似检索了：百度识图 (15)介绍一家新公司：淘淘搜(搜图购) (11)[搜索]5个黑白图像搜索引擎 (14)Tamura纹理特征的原理以及matlab源码 (12)CBIR: Texture Features (0)<table class="wumii-related-items" cellspacing="0" cellpadding="3" border="0"  style="clear: both;">
    
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			<content:encoded><![CDATA[<p>一个是谷歌的：</p>
<p>谷歌将推出一款名为Google Shopper的iPhone应用，配备语音、图像和本地化搜索功能。</p>
<p>谷歌去年曾面向Android平台推出过这款应用，可以根据文本、语音和条形码寻找产品，并进行价格对比。如果搜索“惠普打印机”，便可以获得一系列不同型号的打印机，以及附近的商户列表。谷歌还会根据用户评论显示各个产品的评级。</p>
<p>当用户选定具体某个项目后，Google  Shopper会显示商品的详细信息，用户可以查看售卖相关产品的网上商家或本地商家；一旦用户选择了本地商家，程序将显示各家店铺的存货情况。用户可以 “标记”某个商品，并通过Facebook、Twitter或Google Reader和朋友分享。</p>
<p>和Android版本一样，iPhone版的Shopper速度快、易上手、效率高。不管用户身在何处，程序都可以提供可靠的价格比较。Google Shopper目前已经对ShopSaxy等购物和条形码识别应用产生了威胁。</p>
<p>目前Google Shopper已经登录苹果程序应用商店，系统版本在iOS 4或以上的iPhone可以使用。</p>
<p>再一个是微软的：</p>
<p>微软刚刚宣布了Bing图像搜索去年发布以来的第一次重大更新，实际上微软一直在为图像搜索引擎更新搜索算法和提供共享搜索结果的功能，但这次的功 能改进却直接和用户体验相关，利用标签形式列举的相关关键词可以带来更多具有相关性的图像，并且还更新了布局，可以通过网格的形式确定搜索结果的尺寸。</p>
<p><img title="bing图片搜索" src="http://img.cnbeta.com/newsimg/110125/0758170548947057.png" alt="" width="640" height="320" /><br />
<img title="bing图片搜索" src="http://img.cnbeta.com/newsimg/110125/075820213568728.png" alt="" width="640" height="302" /></p>
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		<title>图像检索垂直应用热了？-淘宝图想</title>
		<link>http://www.zhizhihu.com/html/y2010/2443.html</link>
		<comments>http://www.zhizhihu.com/html/y2010/2443.html#comments</comments>
		<pubDate>Thu, 16 Dec 2010 06:20:19 +0000</pubDate>
		<dc:creator>丕子</dc:creator>
				<category><![CDATA[技术]]></category>
		<category><![CDATA[CBIR]]></category>
		<category><![CDATA[图像检索]]></category>
		<category><![CDATA[基于内容]]></category>
		<category><![CDATA[淘宝图想]]></category>
		<category><![CDATA[百度识图]]></category>

		<guid isPermaLink="false"></guid>
		<description><![CDATA[今天整理reader，发现一条新闻，是淘宝的图像检索，基于电子商务应用的，那我就纳闷了，淘宝有了，那淘淘搜是干什么的呢？淘淘搜不是阿里巴巴旗下的么？哦 可能核心是一样的。 前段时间百度推出了识图，其实用户体验贼差，但是淘宝的图想用户体验那是相当的棒啊，先进的js效果，真是华丽高效。 图想(imagine) 是淘宝近期低调内测的一款图形化搜索引擎，具备以图搜图，相关匹配搜索等个性化功能。 图想(imagine)是淘宝近期低调内测的一款图形化搜索引擎，其技术支持来自于阿里巴巴集团投资入股的杭州淘淘搜团队。以图搜图、图形化相 关匹配搜索是其最大的亮点之一，用户只需要上传或者引用一张图片，便能够在海量的商品数据库中快速找到心仪的宝贝，省去选择关键词描述的流程。另 外，360度，以云图和关联图的方式全方面展示搜索结果，将用户可能关心或者可能喜好的商品一网打尽。目前，图想还处于内测阶段，50枚内测邀请，感兴趣 的同学可以留下电子邮箱。 在写这篇文章的过程中，我才无意中发现淘宝旗下或者冠以淘宝之名的搜索引擎呈现出一种在局外人可能很难看清的产品局部：图想、一淘、淘淘搜、淘宝搜索 等都在各自为阵。毫无疑问，搜索引擎将成为淘宝电子商务平台的最重要的入口，它的推出对于整个大淘宝战略都有着重要的意义；但是现状的情况却是，淘宝相关 的每款搜索产品似乎都有他诞生的特殊背景和使命，但是每款产品似乎又都没有他十分明确的产品以及市场的定位。如果无法清晰这一切，淘宝可能会输掉这场搜索 战役。via cnblogs新闻。 相关文章搜狗互联网图片库2.0（SogouP2.0）正式发布 (4)搜狗竟然也有了基于内容图像检索应用 (3)再收集一下基于内容图像检索系统 (7)最近图像检索应用的新闻 (0)百度竟然推出图像相似检索了：百度识图 (15)介绍一家新公司：淘淘搜(搜图购) (11)[搜索]5个黑白图像搜索引擎 (14)Google Image Swirl-聚类多样性的CBIR (24)Tamura纹理特征的原理以及matlab源码 (12)CBIR: Texture Features (0)<table class="wumii-related-items" cellspacing="0" cellpadding="3" border="0"  style="clear: both;">
    
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			<content:encoded><![CDATA[<p><img class="alignleft" style="border: 1px solid black;" src="http://sd.is.uec.ac.jp/research/intro/cbir/fractal/img2.png" alt="" width="125" height="100" />今天整理reader，发现一条新闻，是淘宝的图像检索，基于电子商务应用的，那我就纳闷了，淘宝有了，那淘淘搜是干什么的呢？淘淘搜不是阿里巴巴旗下的么？哦 可能核心是一样的。</p>
<p>前段时间百度推出了识图，其实用户体验贼差，但是淘宝的图想用户体<span id="more-2443"></span>验那是相当的棒啊，先进的js效果，真是华丽高效。</p>
<p><a href="http://imagine.taobao.com/" target="_blank">图想(imagine)</a> 是淘宝近期低调内测的一款图形化搜索引擎，具备以图搜图，相关匹配搜索等个性化功能。</p>
<p>图想(imagine)是淘宝近期低调内测的一款图形化搜索引擎，其技术支持来自于阿里巴巴集团投资入股的杭州淘淘搜团队。以图搜图、图形化相 关匹配搜索是其最大的亮点之一，用户只需要上传或者引用一张图片，便能够在海量的商品数据库中快速找到心仪的宝贝，省去选择关键词描述的流程。另 外，360度，以云图和关联图的方式全方面展示搜索结果，将用户可能关心或者可能喜好的商品一网打尽。目前，图想还处于内测阶段，50枚内测邀请，感兴趣 的同学可以留下电子邮箱。</p>
<p style="text-align: center;"><img class="aligncenter" src="http://pic003.cnblogs.com/2010/66372/201012/2010121415423178.jpg" alt="" /></p>
<p>在写这篇文章的过程中，我才无意中发现淘宝旗下或者冠以淘宝之名的搜索引擎呈现出一种在局外人可能很难看清的产品局部：图想、<a href="http://www.etao.com/" target="_blank">一淘</a>、<a href="http://www.taotaosou.com/" target="_blank">淘淘搜</a>、<a href="http://search.taobao.com/" target="_blank">淘宝搜索</a> 等都在各自为阵。毫无疑问，搜索引擎将成为淘宝电子商务平台的最重要的入口，它的推出对于整个大淘宝战略都有着重要的意义；但是现状的情况却是，淘宝相关 的每款搜索产品似乎都有他诞生的特殊背景和使命，但是每款产品似乎又都没有他十分明确的产品以及市场的定位。如果无法清晰这一切，淘宝可能会输掉这场搜索 战役。via<a href="http://news.cnblogs.com/n/84560/" target="_blank"> cnblogs新闻</a>。</p>
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			<wfw:commentRss>http://www.zhizhihu.com/html/y2010/2443.html/feed</wfw:commentRss>
		<slash:comments>21</slash:comments>
		</item>
		<item>
		<title>介绍一家新公司：淘淘搜(搜图购)</title>
		<link>http://www.zhizhihu.com/html/y2010/2327.html</link>
		<comments>http://www.zhizhihu.com/html/y2010/2327.html#comments</comments>
		<pubDate>Thu, 04 Nov 2010 12:39:17 +0000</pubDate>
		<dc:creator>丕子</dc:creator>
				<category><![CDATA[创业]]></category>
		<category><![CDATA[技术]]></category>
		<category><![CDATA[CBIR]]></category>
		<category><![CDATA[图像检索]]></category>
		<category><![CDATA[搜图购]]></category>
		<category><![CDATA[机器学习]]></category>
		<category><![CDATA[淘淘搜]]></category>
		<category><![CDATA[购物搜索]]></category>

		<guid isPermaLink="false"></guid>
		<description><![CDATA[由于之前和公司里的一个人交流过，感觉团队不错，自己要是不出去的话也投一投简历试试。 淘淘搜是国内第一个基于视觉计算的图片购物搜索网站！公司成立于2010年4月，是一家以计算机软件研发、技术服务为主的高科技软件型企业。公司擅长图形图像处理、商业智能、企业信息检索管理和电子商务等软 件系统的设计、开发，拥有多项自主知识产权。其中，核心团队在图像识别、处理等领域，拥有多年的研发经验，在国内具有相当的竞争力。 淘淘搜，业务重点在电子商务相关应用领域，与阿里巴巴、淘宝网、人人网等国内著名电子商务相关公司展开合作。2009年底，公司旗下项目---搜图购获得“‘赢在淘宝’TOP应用大赛2009年度总冠军”。 这是一支由博、硕士牵头的年轻团队，快乐、自信、高素质！ 团队成员主要毕业于北大、浙大等著名高校，以博士、硕士为主，并有多位教授、专家参与指导，喜欢钻研国内外顶尖技术及应用，具有很高的技术起点，并与浙江大学等机构有长期人才交流合作。 团队曾为Pfizer、Aventis、Alibaba等世界著名企业提供软件外包服务。 我们坚持“开放、快乐、诚信”的公司文化，坚持“职业化、专业化、规范化”的公司治理理念，不断创新、不断挑战，为打造一家具有中国自主创新标签的著名电子商务应用企业而努力。 确实是一个新公司： 2010年5月 搜图购网站正式更名为淘淘搜，标志着淘淘搜正式进入发展快车道。 2010年4月 淘淘搜正式获得阿里巴巴集团战略投资。 2010年4月 搜图购项目注册成杭州淘淘搜科技有限公司，迅速组成30多人的强势团队，正式进入图像购物搜索领域。 2010年3月 搜图购V1.0正式上线。 2010年1月15日 在北京嘉里中心，搜图购项目在残酷的三轮淘汰赛中脱颖而出， 最终获得评委和现场同行的一致认可，获得“赢在淘宝”2009年TOP应用大赛总冠军。 2009年12月下旬 搜图购强势入围10强。 2009年12月中旬 搜图购，入围30强。 2009年12月上旬 搜图购项目，从3597个开发者，共2246个参赛应用中，顺利进入100强。 2009年10月 完成产品DEMO，参加“赢在淘宝”2009年TOP应用开发大赛。 2009年8月 搜图购（淘淘搜前身）构想正式进行项目立项，开始基础性应用开发可能性研发论证。 相关文章再收集一下基于内容图像检索系统 (7)百度竟然推出图像相似检索了：百度识图 (15)[搜索]5个黑白图像搜索引擎 (14)搜狗互联网图片库2.0（SogouP2.0）正式发布 (4)搜狗竟然也有了基于内容图像检索应用 (3)最近图像检索应用的新闻 (0)图像检索垂直应用热了？-淘宝图想 (21)人的视觉和计算机的视觉 (14)Google Image Swirl-聚类多样性的CBIR (24)Spectral Clustering[谱聚类] (3)<table class="wumii-related-items" cellspacing="0" cellpadding="3" border="0"  style="clear: both;">
    
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</table>]]></description>
			<content:encoded><![CDATA[<p><img class="alignleft" src="http://www.taotaosou.com/style/orange/images/logo.gif" alt="" width="125" height="100" />由于之前和公司里的一个人交流过，感觉团队不错，自己要是不出去的话也投一投简历试试。</p>
<p><a href="http://www.taotaosou.com/" target="_blank">淘淘搜</a>是国内第一个基于视觉计算的图片购物搜索网站！公司成立于2010年4月，是一家以计算机软件研发、技术服务为主的高科技软件型企业。公司擅长图形图像处理、商业智能、<span id="more-2327"></span>企业信息检索管理和电子商务等软 件系统的设计、开发，拥有多项自主知识产权。其中，核心团队在图像识别、处理等领域，拥有多年的研发经验，在国内具有相当的竞争力。</p>
<p>淘淘搜，业务重点在电子商务相关应用领域，与阿里巴巴、淘宝网、人人网等国内著名电子商务相关公司展开合作。2009年底，公司旗下项目---搜图购获得“‘赢在淘宝’TOP应用大赛2009年度总冠军”。</p>
<p><img src="http://www.taotaosou.com/contact/images/company.jpg" border="0" alt="" width="600" /></p>
<p>这是一支由博、硕士牵头的年轻团队，快乐、自信、高素质！</p>
<p>团队成员主要毕业于北大、浙大等著名高校，以博士、硕士为主，并有多位教授、专家参与指导，喜欢钻研国内外顶尖技术及应用，具有很高的技术起点，并与浙江大学等机构有长期人才交流合作。</p>
<p>团队曾为Pfizer、Aventis、Alibaba等世界著名企业提供软件外包服务。</p>
<p>我们坚持“开放、快乐、诚信”的公司文化，坚持“职业化、专业化、规范化”的公司治理理念，不断创新、不断挑战，为打造一家具有中国自主创新标签的著名电子商务应用企业而努力。</p>
<div><img src="http://www.taotaosou.com/contact/images/zp.jpg" alt="" /></div>
<div>确实是一个新公司：</div>
<div>
<div><strong>2010年5月</strong></div>
<div>搜图购网站正式更名为淘淘搜，标志着淘淘搜正式进入发展快车道。</div>
<div><strong>2010年4月</strong></div>
<div>淘淘搜正式获得阿里巴巴集团战略投资。</div>
<div><strong>2010年4月</strong></div>
<div>搜图购项目注册成杭州淘淘搜科技有限公司，迅速组成30多人的强势团队，正式进入图像购物搜索领域。</div>
<div><strong>2010年3月</strong></div>
<div>搜图购V1.0正式上线。</div>
<div><strong>2010年1月15日</strong></div>
<div>在北京嘉里中心，搜图购项目在残酷的三轮淘汰赛中脱颖而出， 最终获得评委和现场同行的一致认可，获得“赢在淘宝”2009年TOP应用大赛总冠军。</div>
<div><strong>2009年12月下旬</strong></div>
<div>搜图购强势入围10强。</div>
<div><strong>2009年12月中旬</strong></div>
<div>搜图购，入围30强。</div>
<div><strong>2009年12月上旬</strong></div>
<div>搜图购项目，从3597个开发者，共2246个参赛应用中，顺利进入100强。</div>
<div><strong>2009年10月</strong></div>
<div>完成产品DEMO，参加“赢在淘宝”2009年TOP应用开发大赛。</div>
<div><strong>2009年8月</strong></div>
<div>搜图购（淘淘搜前身）构想正式进行项目立项，开始基础性应用开发可能性研发论证。</div>
</div>
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		<item>
		<title>[搜索]5个黑白图像搜索引擎</title>
		<link>http://www.zhizhihu.com/html/y2010/1745.html</link>
		<comments>http://www.zhizhihu.com/html/y2010/1745.html#comments</comments>
		<pubDate>Sat, 12 Jun 2010 02:28:42 +0000</pubDate>
		<dc:creator>丕子</dc:creator>
				<category><![CDATA[外语]]></category>
		<category><![CDATA[科研]]></category>
		<category><![CDATA[CBIR]]></category>
		<category><![CDATA[图像检索]]></category>
		<category><![CDATA[搜索引擎]]></category>
		<category><![CDATA[机器学习]]></category>

		<guid isPermaLink="false"></guid>
		<description><![CDATA[图像检索技术在实用领域还是比较少的，特别是比较难的技术，这里收集了几个简单的只是黑白图像检索引擎。英语，不翻译了。 If you share my passion for black and white photography, you will find this toolset especially useful and bookmark-worthy: the top 5 image search engines to find black and white photos. 1. Multicolr Multicolr is a Flickr-based image search engine that allows you to search by color (I’ve already mentioned it previously). To see only [...]<table class="wumii-related-items" cellspacing="0" cellpadding="3" border="0"  style="clear: both;">
    
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			<content:encoded><![CDATA[<p><img class="alignleft" src="http://www.cs.bilkent.edu.tr/%7Esaksoy/images/research/image_contextual_recognition.png" alt="http://www.cs.bilkent.edu.tr/~saksoy/images/research/image_contextual_recognition.png" width="108" height="83" />图像检索技术在实用领域还是比较少的，特别是比较难的技术，这里收集了几个简单的只是黑白图像检索引擎。<span style="color: #ff0000;">英语，不翻译了。</span></p>
<p>If you share my passion for black and white photography, you will find this toolset especially useful and bookmark-worthy: the top 5 <a href="http://www.makeuseof.com/tags/image-search/">image search</a> engines to find black and white photos.<span id="more-1745"></span></p>
<h3>1. Multicolr</h3>
<p><a href="http://labs.ideeinc.com/multicolr/">Multicolr</a> is a Flickr-based image search engine that allows you to search by color (I’ve already mentioned it <a href="http://www.makeuseof.com/tag/16-flickr-search-tools-that-are-fun-to-use/">previously</a>). To see only black and white photography, all you need is to pick colors from the last row:</p>
<p><img src="http://www.makeuseof.com/wp-content/uploads/2010/01/multicolr-500.jpg" alt="black and white image search" width="500" height="277" /></p>
<h3>2. Yahoo Image Search</h3>
<p>Only few people know that Yahoo can be the best Flickr image search engine you’ve ever tried; mainly, because it has some useful search option that Flickr doesn’t. One of them is actually Black&amp;Whit photos. Both options are accessed via Advanced search; there you can set the image color (black and white) and image source (check Flickr to only include photos from Flickr). Right there, you can also set the license filter to only search for images available for distribution:</p>
<p><img src="http://www.makeuseof.com/wp-content/uploads/2010/01/yahoo-image-search-500.jpg" alt="black and white image search" width="500" height="419" /></p>
<h3>3. Corbisimages</h3>
<p><a href="http://www.corbisimages.com/Default.aspx">Corbisimages</a> is my preferred stock images search engine that both contains a high-quality selection of creative photography and offers a robust search feature with lots of features. I first learned about it from this <a href="http://edwardkhoo.com/list-of-best-image-search-engines/">image search engines overview</a> by <a href="http://edwardkhoo.com/">Edward Khoo</a> and it has been my personal favorite since then.</p>
<p>Besides setting it to search through black and white images only, you can filter:</p>
<ul>
<li>By Type (photography or illustration);</li>
<li>By distribution rights (royalty-free or “rights managed”);</li>
<li>By editorial type (current news, documentary, fine art; entertainment):;</li>
<li>By orientation (horizontal, vertical, panorama);</li>
<li>By date when the photo was created;</li>
<li>By photographer.</li>
</ul>
<p><img src="http://www.makeuseof.com/wp-content/uploads/2010/01/corbisimages-500.jpg" alt="black white image search engine" width="500" height="421" /></p>
<h3>4. Bing Image Search</h3>
<p>As an avid Googler, I feel bad listing both Yahoo and Bing and not mentioning Google; but here’s the truth: I love Google general search, I hate Google images search. It is both limited and irrelevant. I prefer Bing Image Search engine.</p>
<p>It has plenty of great search options (including a black and white filter):</p>
<ul>
<li>Search by size (small, medium, large, wallpaper);</li>
<li>Search by layout (squire, tall, wide);</li>
<li>Search by style (photography or illustration);</li>
<li>Check special people search filters: just faces or including head and shoulders.</li>
</ul>
<p>Besides, it offers a similar search option if you hover your mouse cursor over an image.</p>
<p><img src="http://www.makeuseof.com/wp-content/uploads/2010/01/bing-black-white.jpg" alt="free image search engines" width="500" height="407" /></p>
<h3>5. Picsearch</h3>
<p><a href="http://www.picsearch.com/">Picsearch</a> is a good alternative image search engine to have by hand (the tool was already mentioned in our <a href="http://www.makeuseof.com/tag/looking-beyond-google-image-search-5-image-search-engines-for-the-right-image/">alternative image search</a> overview). It doesn’t have any extraordinary search options to mention. The only reason I use it from time to time is that it provides totally different search results – something I’d never be able to find using ordinary tools like Google or Yahoo.</p>
<p>Picsearch uses its own search index and operates its own “unique search technology”:</p>
<blockquote><p>Picsearch uses its own technology to crawl the web and has created a searchable index of images…. Picsearch image search technology has three main features that make it unique. It has a relevancy unrivalled on the web due to its patent-pending indexing algorithms. Also, Picsearch has a family friendliness that allows children to surf in safety as all offensive material is filtered out by our advanced filtering systems. The site is also very user friendly as it’s designed to be simple, fast and accurate.</p></blockquote>
<p>Besides searching for black and white photography, the tool offers a few other nifty features like:</p>
<ul>
<li>Filtering by size;</li>
<li>Filtering by type (landscape versus portrait for example);</li>
<li>Showing search suggestions.</li>
</ul>
<p><img src="http://www.makeuseof.com/wp-content/uploads/2010/01/picsearch-500.jpg" alt="free image search engines" width="500" height="377" /></p>
<p>What are you favourite image search engines? Tell us about them in the comments.<a href="http://www.makeuseof.com/tags/image-search/" target="_blank">原文</a></p>
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		<slash:comments>14</slash:comments>
		</item>
		<item>
		<title>Google Image Swirl-聚类多样性的CBIR</title>
		<link>http://www.zhizhihu.com/html/y2010/1573.html</link>
		<comments>http://www.zhizhihu.com/html/y2010/1573.html#comments</comments>
		<pubDate>Wed, 28 Apr 2010 12:58:28 +0000</pubDate>
		<dc:creator>丕子</dc:creator>
				<category><![CDATA[技术]]></category>
		<category><![CDATA[CBIR]]></category>
		<category><![CDATA[Google]]></category>
		<category><![CDATA[Image Swirl]]></category>
		<category><![CDATA[图像检索]]></category>
		<category><![CDATA[机器视觉]]></category>

		<guid isPermaLink="false"></guid>
		<description><![CDATA[Google Image Swirl利用算法、关键词和脸部识别来区分建筑、地点、人员，甚至可以知道图片中的时间。例如，搜索关键词“华盛顿”后，Image Swirl会将图片分成几组，包括“白宫”、“乔治-华盛顿”、“丹泽尔-华盛顿”（美国著名演员）等。点击这些分组后，用户可以看到更详细的分类，如角 度、图片中的时间、特写还是全景等。 利用该服务，用户在键入关键词后，将得到同一主题的图片搜索结果，同时可获得更多图片显示排列方式，以提高用户搜索 体验。 谷歌称，以各类图片所拍摄地点、拍摄内容相似性为标准，Swirl服务将把各类图片加以分类，该分类还可包括多 级子分类，同时提供不同的用户界面。此前谷歌曾推出文本内容的分类搜索，其名称为“Wonder Wheel”。而Swirl可视为Wonder Wheel服务的延伸，即把文本分类搜索的理念引入到图片搜索当中。 谷歌技术团队表示，与谷歌常规图片搜索所不同的是，用户在键入关键词后，可得到大量同一主题的图片，如果感觉这 些图片之间的相关程度并不高，则可点击其中一幅较符合自己要求的图片，则该搜索引擎又会返回同图片更相关的大量图片。此时用户界面变成了以该图片为中心， 四周将出现更多相似图片，周围这些图片本身又附加上一些尺寸更小的相似图片(即子分类)。 谷歌推出同一主题图片搜索服务Image Swirl 相关文章最近图像检索应用的新闻 (0)搜狗互联网图片库2.0（SogouP2.0）正式发布 (4)搜狗竟然也有了基于内容图像检索应用 (3)再收集一下基于内容图像检索系统 (7)图像检索垂直应用热了？-淘宝图想 (21)百度竟然推出图像相似检索了：百度识图 (15)介绍一家新公司：淘淘搜(搜图购) (11)Google新图像检索发布视频 (18)再次关注Google图像检索&#8211;嵌入广告 (10)[搜索]5个黑白图像搜索引擎 (14)<table class="wumii-related-items" cellspacing="0" cellpadding="3" border="0"  style="clear: both;">
    
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			<content:encoded><![CDATA[<p><a href="http://www.zhizhihu.com/wp-content/uploads/2009/12/google.gif"><img class="alignleft size-full wp-image-966" title="google" src="http://www.zhizhihu.com/wp-content/uploads/2009/12/google.gif" alt="" width="104" height="38" /></a><a href="http://image-swirl.googlelabs.com/" target="_blank">Google Image Swirl</a>利用算法、关键词和脸部识别来区分建筑、地点、人员，甚至可以知道图片中的时间。例如，搜索关键词“华盛顿”后，Image  Swirl会将图片分成几组，包括“白宫”、“乔治-华盛顿”、“丹泽尔-华盛顿”（美国著名演员）等。点击这些分组后，用户可以看到更详细的分类，如角 度、图片中的时间、特写还是全景等。</p>
<p><span>利用该服务，用户在键入关键词后，将得到同一主题的图片搜索结果，同时可获得更多图片显示排列方式，以提高用户搜索 体验。</span></p>
<p><span> 谷歌称，以各类图片所拍摄地点、拍摄内容相似性为标准，Swirl服务将把各类图片加以分类，该分类还可包括多 级子分类，同时提供不同的用户界面。此前谷歌曾推出文本内容的分类搜索，其名称为“Wonder Wheel”。而Swirl可视为Wonder  Wheel服务的延伸，即把文本分类搜索的理念引入到图片搜索当中。<span id="more-1573"></span></span></p>
<p><span> 谷歌技术团队表示，与谷歌常规图片搜索所不同的是，用户在键入关键词后，可得到大量同一主题的图片，如果感觉这 些图片之间的相关程度并不高，则可点击其中一幅较符合自己要求的图片，则该搜索引擎又会返回同图片更相关的大量图片。此时用户界面变成了以该图片为中心， 四周将出现更多相似图片，周围这些图片本身又附加上一些尺寸更小的相似图片(即子分类)。</span></p>
<p style="text-align: center;"><span style="font-size: x-small;"> <img class="aligncenter" src="http://news.newhua.com/Files/Remoteupfile/2009-11/18/24035683.jpg" alt="谷歌推出主题图片搜索服务Image Swirl(组图)" width="400" height="443" /></span></p>
<p style="text-align: center;"><span style="font-size: x-small;"> <img class="aligncenter" src="http://news.newhua.com/Files/Remoteupfile/2009-11/18/24035685.jpg" alt="谷歌推出主题图片搜索服务Image Swirl(组图)" width="400" height="279" /></span></p>
<p style="text-align: center;"><span style="font-size: x-small;"> <img class="aligncenter" src="http://news.newhua.com/Files/Remoteupfile/2009-11/18/24035687.jpg" alt="谷歌推出主题图片搜索服务Image Swirl(组图)" width="400" height="270" /></span></p>
<p style="text-align: center;"><span style="font-size: x-small;">谷歌推出同一主题图片搜索服务Image Swirl</span></p>
<div id="_mcePaste" style="position: absolute; left: -10000px; top: 232px; width: 1px; height: 1px; overflow: hidden;"><img src="file:///C:/DOCUME%7E1/Page/LOCALS%7E1/Temp/moz-screenshot-1.png" alt="" /></div>
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		<title>Tamura纹理特征的原理以及matlab源码</title>
		<link>http://www.zhizhihu.com/html/y2010/1134.html</link>
		<comments>http://www.zhizhihu.com/html/y2010/1134.html#comments</comments>
		<pubDate>Mon, 18 Jan 2010 02:58:19 +0000</pubDate>
		<dc:creator>丕子</dc:creator>
				<category><![CDATA[科研]]></category>
		<category><![CDATA[CBIR]]></category>
		<category><![CDATA[Matlab]]></category>
		<category><![CDATA[tamura]]></category>
		<category><![CDATA[图像检索]]></category>
		<category><![CDATA[纹理特征]]></category>

		<guid isPermaLink="false"></guid>
		<description><![CDATA[    上图是灰度共生矩阵的原理图。 原理可以详细阅读有关论文，这里有详细介绍：查看链接 基于人类对纹理的视觉感知的心理学的研究，Tamura等人提出了纹理特征的表达[14]。Tamura纹理特征的六个分量对应于心理学角度上纹理特征的六种属性，分别是粗糙度（coarseness）、对比度（contrast）、方向度（directionality）、 线像度（linelikeness）、规整度（regularity）和粗略度（roughness）。其中，前三个分量对于图像检索尤其重要 代码比较好的发现新浪芮萌同学的博客，详细介绍了这六个维度的实现。 Tamura纹理特征的matlab实现（一）---粗糙度 Tamura纹理特征的matlab实现（二）---对比度 Tamura纹理特征的matlab实现（三）---方向度 Tamura纹理特征的matlab实现（四）---线性度 Tamura纹理特征的matlab实现（五）---规则度 Tamura纹理特征的matlab实现（六）---粗略度 相关文章Gray-level Co-occurrence Matrix(灰度共生矩阵) (1)CBIR: Texture Features (0)搜狗互联网图片库2.0（SogouP2.0）正式发布 (4)搜狗竟然也有了基于内容图像检索应用 (3)再收集一下基于内容图像检索系统 (7)最近图像检索应用的新闻 (0)图像检索垂直应用热了？-淘宝图想 (21)介绍一家新公司：淘淘搜(搜图购) (11)[搜索]5个黑白图像搜索引擎 (14)Google Image Swirl-聚类多样性的CBIR (24)<table class="wumii-related-items" cellspacing="0" cellpadding="3" border="0"  style="clear: both;">
    
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			<content:encoded><![CDATA[<p style="text-align: center;"><img src="http://www.cs.auckland.ac.nz/compsci708s1c/lectures/Glect-html/glch.gif" border="0" alt="" align="center" /> </p>
<p style="text-align: center;"> </p>
<p style="text-align: center;">上图是灰度共生矩阵的原理图。<span id="more-1134"></span></p>
<p>原理可以详细阅读有关论文，这里有详细介绍：<a href="http://www.cs.auckland.ac.nz/compsci708s1c/lectures/Glect-html/topic4c708FSC.htm#tamura" target="_blank">查看链接</a></p>
<p>基于人类对纹理的视觉感知的心理学的研究，Tamura等人提出了纹理特征的表达[14]。Tamura纹理特征的六个分量对应于心理学角度上纹理特征的六种属性，分别是粗糙度（coarseness）、对比度（contrast）、方向度（directionality）、 线像度（linelikeness）、规整度（regularity）和粗略度（roughness）。其中，前三个分量对于图像检索尤其重要</p>
<p>代码比较好的发现新浪<a href="http://blog.sina.com.cn/xuruimeng">芮萌</a>同学的博客，详细介绍了这六个维度的实现。</p>
<div><a href="http://blog.sina.com.cn/s/blog_59ead5d90100gx1d.html~type=v5_one&amp;label=rela_prevarticle" target="_blank">Tamura纹理特征的matlab实现（一）---粗糙度</a></div>
<div>
<div><a href="http://blog.sina.com.cn/s/blog_59ead5d90100gx4v.html~type=v5_one&amp;label=rela_nextarticle" target="_blank">Tamura纹理特征的matlab实现（二）---对比度</a></div>
<div>
<div><a href="http://blog.sina.com.cn/s/blog_59ead5d90100gxkc.html~type=v5_one&amp;label=rela_nextarticle" target="_blank">Tamura纹理特征的matlab实现（三）---方向度</a></div>
<div>
<div><a href="http://blog.sina.com.cn/s/blog_59ead5d90100gxke.html~type=v5_one&amp;label=rela_nextarticle" target="_blank">Tamura纹理特征的matlab实现（四）---线性度</a></div>
<div>
<div><a href="http://blog.sina.com.cn/s/blog_59ead5d90100gxkj.html~type=v5_one&amp;label=rela_nextarticle" target="_blank">Tamura纹理特征的matlab实现（五）---规则度</a></div>
<div>
<div><a href="http://blog.sina.com.cn/s/blog_59ead5d90100gxkl.html~type=v5_one&amp;label=rela_nextarticle" target="_blank">Tamura纹理特征的matlab实现（六）---粗略度</a></div>
</div>
</div>
</div>
</div>
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		<comments>http://www.zhizhihu.com/html/y2010/1133.html#comments</comments>
		<pubDate>Mon, 18 Jan 2010 02:34:54 +0000</pubDate>
		<dc:creator>丕子</dc:creator>
				<category><![CDATA[科研]]></category>
		<category><![CDATA[CBIR]]></category>
		<category><![CDATA[GLCM]]></category>
		<category><![CDATA[tamura]]></category>
		<category><![CDATA[texture]]></category>
		<category><![CDATA[图像检索]]></category>

		<guid isPermaLink="false"></guid>
		<description><![CDATA[搜索了下图像的纹理特征，下面的资源讲得很详细很不错很综述。 QBE Using Texture Features Texture Description Texture Features and Co-occurrence Matrices Tamura's Texture Features Markov Random Field Texture Models Similarity Measures for Texture Features Wold Decomposition Based and Gabor Texture Features MPEG-7 Texture Descriptors Texture Browsing Descriptor Homogeneous Texture Descriptor Edge Histogram Descriptor References 相关文章Tamura纹理特征的原理以及matlab源码 (12)Gray-level Co-occurrence Matrix(灰度共生矩阵) (1)搜狗互联网图片库2.0（SogouP2.0）正式发布 (4)搜狗竟然也有了基于内容图像检索应用 (3)再收集一下基于内容图像检索系统 (7)最近图像检索应用的新闻 (0)图像检索垂直应用热了？-淘宝图想 (21)介绍一家新公司：淘淘搜(搜图购) [...]<table class="wumii-related-items" cellspacing="0" cellpadding="3" border="0"  style="clear: both;">
    
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			<content:encoded><![CDATA[<p>搜索了下图像的纹理特征，下面的资源讲得很详细很不错很综述。</p>
<li><a href="http://www.cs.auckland.ac.nz/compsci708s1c/lectures/Glect-html/topic4c708FSC.htm#texture-rep">QBE Using Texture Features</a>
<ul>
<li><a href="http://www.cs.auckland.ac.nz/compsci708s1c/lectures/Glect-html/topic4c708FSC.htm#descript">Texture Description</a></li>
<li><a href="http://www.cs.auckland.ac.nz/compsci708s1c/lectures/Glect-html/topic4c708FSC.htm#cooc">Texture Features and Co-occurrence Matrices</a></li>
<li><a href="http://www.cs.auckland.ac.nz/compsci708s1c/lectures/Glect-html/topic4c708FSC.htm#tamura">Tamura's Texture Features</a></li>
<li><a href="http://www.cs.auckland.ac.nz/compsci708s1c/lectures/Glect-html/topic4c708FSC.htm#mrf">Markov Random Field Texture Models</a></li>
<li><a href="http://www.cs.auckland.ac.nz/compsci708s1c/lectures/Glect-html/topic4c708FSC.htm#simmeasure">Similarity Measures for Texture Features</a></li>
<li><a href="http://www.cs.auckland.ac.nz/compsci708s1c/lectures/Glect-html/topic4c708FSC.htm#wold">Wold Decomposition Based and Gabor Texture Features</a></li>
</ul>
</li>
<li><a href="http://www.cs.auckland.ac.nz/compsci708s1c/lectures/Glect-html/topic4c708FSC.htm#mpeg">MPEG-7 Texture Descriptors</a>
<ul>
<li><a href="http://www.cs.auckland.ac.nz/compsci708s1c/lectures/Glect-html/topic4c708FSC.htm#browse">Texture Browsing Descriptor</a></li>
<li><a href="http://www.cs.auckland.ac.nz/compsci708s1c/lectures/Glect-html/topic4c708FSC.htm#homogen">Homogeneous Texture Descriptor</a></li>
<li><a href="http://www.cs.auckland.ac.nz/compsci708s1c/lectures/Glect-html/topic4c708FSC.htm#edge">Edge Histogram Descriptor</a></li>
</ul>
</li>
<li><a href="http://www.cs.auckland.ac.nz/compsci708s1c/lectures/Glect-html/topic4c708FSC.htm#refs">References</a></li>
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