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		<doi>10.1109/SIBGRA.2000.883917</doi>
		<citationkey>NehabGatt:2000:RaPaCa</citationkey>
		<title>Ray path categorization</title>
		<year>2000</year>
		<numberoffiles>1</numberoffiles>
		<size>883 KiB</size>
		<author>Nehab, Diego,</author>
		<author>Gattass, Marcelo,</author>
		<editor>Carvalho, Paulo Cezar Pinto,</editor>
		<editor>Walter, Marcelo,</editor>
		<conferencename>Brazilian Symposium on Computer Graphics and Image Processing, 13 (SIBGRAPI)</conferencename>
		<conferencelocation>Gramado, RS, Brazil</conferencelocation>
		<date>17-20 Oct. 2000</date>
		<publisher>IEEE Computer Society</publisher>
		<publisheraddress>Los Alamitos</publisheraddress>
		<pages>227-234</pages>
		<booktitle>Proceedings</booktitle>
		<tertiarytype>Full Paper</tertiarytype>
		<organization>SBC - Brazilian Computer Society</organization>
		<transferableflag>1</transferableflag>
		<versiontype>finaldraft</versiontype>
		<keywords>edge detection, ray path categorization, edge detection, image segmentation algorithms, geometrical information extraction, pixel colors, ray-traced images, geometrical information, image rendering, equivalence classes, category information, rendering process, detected edges, aliasing, ray tracer, memory requirements.</keywords>
		<abstract>Edge detection and image segmentation algorithms usually operate on an image to extract geometrical information based on pixel colors. For ray-traced images, the presence of geometrical information on the scene from which the image was rendered allows for a completely different approach. We present an algorithm that divides rays into equivalence classes, or categories. The category information is generated during the rendering process and used to determine edges in the resulting image. Detected edges can later be used to help determine areas subject to aliasing. Little effort is needed to implement the described algorithms over an existing ray tracer. Furthermore, the extra computational and memory requirements are modest.</abstract>
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		<notes>The conference was held in Gramado, RS, Brazil, from October 17 to 20.</notes>
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		<url>http://sibgrapi.sid.inpe.br/rep-/sid.inpe.br/banon/2002/11.13.11.36</url>
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