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		<site>sibgrapi.sid.inpe.br 802</site>
		<identifier>8JMKD3MGPAW/3PH2NFL</identifier>
		<repository>sid.inpe.br/sibgrapi/2017/08.29.01.15</repository>
		<lastupdate>2017:08.29.01.15.25 sid.inpe.br/banon/2001/03.30.15.38 luiz.buschetto@grad.ufsc.br</lastupdate>
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		<citationkey>MacariniWebe:2017:QuCoSy</citationkey>
		<title>Quality Control System for Ceramic Tiles using Segmentation-based Fractal Texture Analysis and SVM</title>
		<format>On-line</format>
		<year>2017</year>
		<numberoffiles>1</numberoffiles>
		<size>429 KiB</size>
		<author>Macarini, Luiz Antonio,</author>
		<author>Weber, Tiago Oliveira,</author>
		<affiliation>Universidade Federal de Santa Catarina</affiliation>
		<affiliation>Universidade Federal de Santa Catarina</affiliation>
		<editor>Torchelsen, Rafael Piccin,</editor>
		<editor>Nascimento, Erickson Rangel do,</editor>
		<editor>Panozzo, Daniele,</editor>
		<editor>Liu, Zicheng,</editor>
		<editor>Farias, Mylène,</editor>
		<editor>Viera, Thales,</editor>
		<editor>Sacht, Leonardo,</editor>
		<editor>Ferreira, Nivan,</editor>
		<editor>Comba, João Luiz Dihl,</editor>
		<editor>Hirata, Nina,</editor>
		<editor>Schiavon Porto, Marcelo,</editor>
		<editor>Vital, Creto,</editor>
		<editor>Pagot, Christian Azambuja,</editor>
		<editor>Petronetto, Fabiano,</editor>
		<editor>Clua, Esteban,</editor>
		<editor>Cardeal, Flávio,</editor>
		<e-mailaddress>luiz.buschetto@grad.ufsc.br</e-mailaddress>
		<conferencename>Conference on Graphics, Patterns and Images, 30 (SIBGRAPI)</conferencename>
		<conferencelocation>Niterói, RJ</conferencelocation>
		<date>Oct. 17-20, 2017</date>
		<booktitle>Proceedings</booktitle>
		<publisher>Sociedade Brasileira de Computação</publisher>
		<publisheraddress>Porto Alegre</publisheraddress>
		<tertiarytype>Industry Application Paper</tertiarytype>
		<transferableflag>1</transferableflag>
		<keywords>Image Processing, Machine Learning, SFTA, Ceramic Tiles, Defect Detection.</keywords>
		<abstract>The ceramic industry has a highly automated production system. The quality control, however, is still performed by humans, which limits its speed and precision. This work proposes a complete verification system for ceramic tiles based on image processing and machine learning. The system has four steps: image acquisition, pre-processing, feature extraction and classification. The feature extraction step uses Segmentation-based Fractal Texture Analysis (SFTA). A Support Vector Machine is employed to classify the ceramic tiles. The system is implemented using OpenCV libraries. In total, 783 ceramic tiles were used, being 80% for training and 20% to testing. The present work had reached the proposed objectives, both in processing time and accuracy, achieving 98.68% of detection rate.</abstract>
		<language>en</language>
		<targetfile>SIBGRAPI_Luiz_Tiago.pdf</targetfile>
		<usergroup>luiz.buschetto@grad.ufsc.br</usergroup>
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		<url>http://sibgrapi.sid.inpe.br/rep-/sid.inpe.br/sibgrapi/2017/08.29.01.15</url>
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