文章基本信息

标题：The Framework of Image Recognition based on Modified Freeman Chain Code
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作者：Mr. Haswadi Hasan ; Associate Professor Habibollah Haron ; Associate Professor Siti Zaiton Mohd Hashim 等
期刊名称：International Journal of Image Processing (IJIP)
电子版ISSN：1985-2304
出版年度：2011
卷号：5
期号：5
页码：542-551
出版社：Computer Science Journals
摘要：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.
关键词：Corner Detection; Chain Code; Line Drawing; Feature Extraction; Recognition