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		<isbn>978-85-17-00088-1</isbn>
		<label>59371</label>
		<citationkey>ZanottaSarDiaFrePin:2017:ClSuBa</citationkey>
		<title>Classificação supervisionada com base em atributos cognitivos de cor para imagens de sensoriamento remoto</title>
		<format>Internet</format>
		<year>2017</year>
		<secondarytype>PRE CN</secondarytype>
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		<author>Zanotta, Daniel Capella Capella,</author>
		<author>Sartorio, Letícia Figueiredo,</author>
		<author>Dias, Fabiano Soares,</author>
		<author>Freitas, Bruna dos Santos,</author>
		<author>Pintado, Tamires Pereira,</author>
		<electronicmailaddress>daniel.zanotta@riogrande.ifrs.edu.br</electronicmailaddress>
		<editor>Gherardi, Douglas Francisco Marcolino,</editor>
		<editor>Aragão, Luiz Eduardo Oliveira e Cruz de,</editor>
		<e-mailaddress>daniela.seki@inpe.br</e-mailaddress>
		<conferencename>Simpósio Brasileiro de Sensoriamento Remoto, 18 (SBSR)</conferencename>
		<conferencelocation>Santos</conferencelocation>
		<date>28-31 maio 2017</date>
		<publisher>Instituto Nacional de Pesquisas Espaciais (INPE)</publisher>
		<publisheraddress>São José dos Campos</publisheraddress>
		<pages>7416-7423</pages>
		<booktitle>Anais</booktitle>
		<organization>Instituto Nacional de Pesquisas Espaciais (INPE)</organization>
		<transferableflag>1</transferableflag>
		<abstract>This work aims at present a new classification method based on cognitive color attributes. Implemented in a supervised manner, the method assumes user collected samples for unlimited number of classes in a three dimensional space of attributes. Then, the samples are converted to HSV and plotted in a simplified two dimensional HSV diagram. The user has to select polygons on this reduced HSV space in order to generalize the scope of each class. Finally, the original image is all converted to HSV space and each element is considered in order to define if it lies in a region occupied by one class in the reduced HSV space. The main advantage of the proposed classification process is the power to emulate the human ability to acquiring knowledge and understanding through thought, experience, and the senses (cognitive aspects) used by photo interpreters during visual interpretation of remote sensing image targets. For this reason, the limited space of attributes is necessary, that is, to match the number of channels showed at screen. Experiments performed with an image marked by deforestation in Amazon were conducted by comparing the performance of several classification approaches. The method proved to be useful for noncomplex problems when simple approaches tend to show adequate results. Other advantages of the proposed method is its simplicity, its intuitiveness, besides it ability to generalize the sampling process in applications which collecting homogeneous samples is a difficult task.</abstract>
		<area>SRE</area>
		<type>Classificação e mineração de dados</type>
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