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	<title>動的プログラミング Archives &#8212; MATLAB Number ONE</title>
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	<title>動的プログラミング Archives &#8212; MATLAB Number ONE</title>
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		<title>Automatic Image Segmentation by Dynamic Region Merging</title>
		<link>https://matlab1.com/shop/matlab-code/automatic-image-segmentation-by-dynamic-region-merging/</link>
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		<dc:creator><![CDATA[global MATLAB]]></dc:creator>
		<pubDate>Tue, 08 May 2018 05:32:39 +0000</pubDate>
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					<description><![CDATA[<p>In this project, we proposed a novel method for segmenting an image into distinct components. The proposed algorithm is implemented in a region merging style. We defined a merging predicate P for the evidence of a merging between two neighboring regions. This predicate was defined by the sequential probability ratio test (SPRT) and the maximum likelihood criterion. [&#8230;]</p>
<p>The post <a href="https://matlab1.com/shop/matlab-code/automatic-image-segmentation-by-dynamic-region-merging/">Automatic Image Segmentation by Dynamic Region Merging</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
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		<title>Rotation Invariant Nonrigid Point Set Matching in Cluttered Scenes</title>
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		<dc:creator><![CDATA[global MATLAB]]></dc:creator>
		<pubDate>Mon, 16 Apr 2018 04:27:57 +0000</pubDate>
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					<description><![CDATA[<p>To address the problem of rotation invariant nonrigid point set matching, we proposed two methods for shape representation. The shape context (SC) feature descriptor was used and we constructed graphs on point sets where edges are used to determine the orientations of SCs. This enables the proposed methods rotation invariant. The structures of our shape representations facilitate the use of DP [&#8230;]</p>
<p>The post <a href="https://matlab1.com/shop/matlab-code/rotation-invariant-nonrigid-point-set-matching-in-cluttered-scenes/">Rotation Invariant Nonrigid Point Set Matching in Cluttered Scenes</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
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