Experimental Analysis of the Modified Direction Feature for Cursive Character Recognition
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This paper describes and analyzes the performance of a structural feature extraction technique for the recognition of segmented/cursive characters that may be used in the context of a segmentation-based, handwritten word recognition system. The Modified Direction Feature (MDF) extraction technique builds upon a previous technique proposed by the authors that extracts direction information from the structure of character contours. This principle is extended so that the direction information is integrated with a technique for detecting transitions between background and foreground pixels in the character image. The MDF technique used in conjunction with neural network classifiers provide recognition rates of up to 90.24%, which are amongst the highest in the literature. This paper also presents a detailed analysis of the characters that were the source of misclassification in the character recognition process. The characters used for experimentation were obtained from the CEDAR benchmark database.
Proceedings of the 9th Int'l Workshop on Frontiers in Handwriting Recognition (IWFHR-9 2004)
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