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The Framework of Image Recognition based on Modified Freeman Chain Code
Haswadi Hasan, Habibollah Haron, Siti Zaiton Mohd Hashim
Pages - 542 - 551     |    Revised - 01-11-2011     |    Published - 15-12-2011
Volume - 5   Issue - 5    |    Publication Date - November / December 2011  Table of Contents
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KEYWORDS
Corner Detection, Chain Code, Line Drawing, Feature Extraction, Recognition
ABSTRACT
Image recognition of line drawing involves feature extraction and feature comparison. Works on the extraction required the representation of the image to be compared. Combining these two requirements, a framework that develops a new extraction algorithm of a chain code representation is presented. In addition, new corner detection is presented as pre-processing to the line drawing input in order to derive the chain code. This paper presents a new framework that consist of five steps namely pre-processing and image processing, new corner detection algorithm, chain code generator, feature extraction algorithm, and recognition process. Heuristic approach that is applied in the corner detection algorithm accepts input of thinned binary image and produce a modified thinned binary image consisted of J character to represent corners in the image. Using the modified thinned binary image, a new chain code scheme that is based on Freeman chain code is proposed and an algorithm is developed to generate a single chain code series that is representing the line drawing input. The feature extraction algorithm is then extracting the three pre-defined features of the chain code for recognition purpose. The features are corner properties, distance between corners, and angle from a corner to the connected corner. The explanation of steps in the framework is supported with two line drawings. The results show that the framework successfully recognizes line drawing into five categories namely not similar line drawing, and four other categories that are similar but with attributes of rotation angle and scaling ratio.
CITED BY (2)  
1 Radha, R., & Aparna, R. R. (2014). Automatic extraction, segmentation and recognition of multi-font Indian Pincode. International Journal of Computational Vision and Robotics, 4(3), 247-258.
2 Radha, R., & Aparna, R. R. (2012). Enchanced Automatic Offline Character Image Pre-processing and Recogintion Using Single Layer Network. International Journal of Advanced Research in Computer Science, 3(4).
1 Google Scholar 
2 CiteSeerX 
3 refSeek 
4 Scribd 
5 SlideShare 
6 PdfSR 
1 Yueh-Ling Lin and Mao-Jiun J. Wang, "Automatic Feature Extraction from Front and Side Images", Industrial Engineering and Engineering Management, 2008. IEEM 2008. p1949,2008.
2 Junding, Sun and Heli, Xu; "Contour-Shape Recognition and Retrieval Based on Chain Code", 2009 International Conference on Computational Intelligence and Security, p349-352, 2009.
3 Yong-Xianga Sun; Cheng-Minga Zhang; Ping-Zenga Liu; Hong-Mei Zhu; "Shape feature extraction of fruit image based on chain code", Proceedings of the 2007 International Conference on Wavelet Analysis and Pattern Recognition, Beijing, vol3, p1346 - 1349,2007.
4 Chalechale, A.; Naghdy, G.; Premaratne, P.; Moghaddasi, H.; "Chain-based extraction of line segments to describe images", 2004 IEEE International Conference on Multimedia and Expo (ICME), Page(s): 355 - 358 Vol.1, 2004.
5 Tie-Gen Peng; Ti-Hua Wu; Yong Luo; "The method based on boundary chain-code for objects recognition and gesture analysis", Proceedings of the Third International Conference on Mache Learning and Cybernetics, p3700 - 3705 vol.6, 2004.
6 Bo Yu; Lei Guo, Xiaoliang Qian and Tianyun Zhao, "A Corner Detection Algorithm Based on the Difference of FCC", 2010, International Conference On Computer Design And Applications (ICCDA 2010), vol 4, Page(s): V4-226 - V4-229, 2010.
7 Nain, N.; Laxmi, V.; Bhadviya, B.; Gopal, A.; "Corner Detection using Difference Chain Code as Curvature", Third International IEEE Conference on Signal-Image Technologies and Internet-Based System, p821 - 825, 2007.
8 Wang Xiaoling and Xie Kanglin, "A novel direction chain code-based image retrieval", Fourth International Conference on Computer and Information Technology (CIT04), p190 - 193,2004.
Mr. Haswadi Hasan
Universiti Teknologi Malaysia - Malaysia
haswadi@utm.my
Associate Professor Habibollah Haron
- Malaysia
Associate Professor Siti Zaiton Mohd Hashim
- Malaysia