OS20-2 Color and Shape based Method for Detecting and Classifying Card Images

Title:	OS20-2 Color and Shape based Method for Detecting and Classifying Card Images
Publication:	ICAROB2017
Volume:	22
Pages:	307-310
ISSN:	2188-7829
DOI:	10.5954/ICAROB.2017.OS20-2
Author(s):	Cho Nilar Phyo, Thi Thi Zin, Hiroshi Kamada, Takashi Toriu
Publication Date:	January 19, 2017
Keywords:	color segmentation, shape classification, interactive e-learning
Abstract:	This paper proposes an effective method for detecting and classifying card images by using color and shape features. We extract the card color area using color information and remove low possibility regions based on shape feature. Then, we classify the image by taking classroom size and camera distance. In order to confirm the proposed method, we conduct the experiments with our own videos. Our experimental results show that the proposed method is very promising compared to some existing methods.
PDF File:	https://alife-robotics.co.jp/members2017/icarob/data/html/data/OS_pdf/OS20/OS20-2.pdf
Copyright:	© The authors. This article is distributed under the terms of the Creative Commons Attribution License 4.0, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited. See for details: https://creativecommons.org/licenses/by-nc/4.0/