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		<doi>10.1109/SIBGRA.2004.1352951</doi>
		<citationkey>JungSchr:2004:ReDeBa</citationkey>
		<title>Rectangle Detection based on a Windowed Hough Transform</title>
		<format>On-line</format>
		<year>2004</year>
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		<author>Jung, Cláudio Rosito,</author>
		<author>Schramm, Rodrigo,</author>
		<affiliation>UNISINOS - Universidade do Vale do Rio dos Sinos - Ciências Exatas e Tecnológicas</affiliation>
		<editor>Araújo, Arnaldo de Albuquerque,</editor>
		<editor>Comba, João Luiz Dihl,</editor>
		<editor>Navazo, Isabel,</editor>
		<editor>Sousa, Antônio Augusto de,</editor>
		<e-mailaddress>crjung@exatas.unisinos.br</e-mailaddress>
		<conferencename>Brazilian Symposium on Computer Graphics and Image Processing, 17 (SIBGRAPI) - Ibero-American Symposium on Computer Graphics, 2 (SIACG)</conferencename>
		<conferencelocation>Curitiba, PR, Brazil</conferencelocation>
		<date>17-20 Oct. 2004</date>
		<publisher>IEEE Computer Society</publisher>
		<publisheraddress>Los Alamitos</publisheraddress>
		<booktitle>Proceedings</booktitle>
		<tertiarytype>Full Paper</tertiarytype>
		<transferableflag>1</transferableflag>
		<versiontype>finaldraft</versiontype>
		<keywords>rectangle detection, windowed Hough Transform.</keywords>
		<abstract>The problem of detecting rectangular structures in images arises in many applications, from building extraction in aerial images to particle detection in cryo-electron microscopy. This paper proposes a new technique for rectangle detection using a windowed Hough Transform. Every pixel of the image is scanned, and a sliding window is used to compute the Hough Transform of small regions of the image. Peaks of the Hough image (which correspond to line segments) are then extracted, and a rectangle is detected when four extracted peaks satisfy certain geometric conditions. Experimental results indicate that the proposed technique produced promising results for both synthetic and natural images.</abstract>
		<language>en</language>
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