Joong Jo Park

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This paper presents a method to recognize the various defect patterns of a cold mill strip using a binary decision tree constructed by genetic algo-rithm(GA). In this paper, GA was used to select a subset of the suitable features at each node in the binary decision tree. The feature subset with maximum fitness is chosen and the patterns are divided into two(More)
Off-line handwritten numeral recognition is a very difficult task. It is hard to achieve high recognition results using a single set of features and a single classifier, since handwritten numerals contain many pattern variations which mostly depend upon individual writing styles. In this paper, we propose a recognition system using hybrid features and a(More)
This paper proposes a method to recognize the various defect patterns of a cold mill strip using a binary decision. In classifying complex patterns with high similarity like these defect patterns, the selection of an optimal feature set and an appropriate recognizer is a prerequisite to a high recognition rate. In this paper GA and K-means algorithm were(More)
In object analysis, line and curve finding plays a universal role, and it can be accomplished by detecting ridges and ravines in digital gray scale images. In this paper, we present a new method of detecting ridges and ravines by using local min and max operations. This method uses erosion and dilation properties of fuzzy logic operations and requires no(More)
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