Pre and Post Processing Approaches in Edge Detection for Character Recognition

This paper deals with the recognition of handwritten Malayalam characters. Most of the pattern recognition systems will go through the steps like preprocessing, feature extraction and classification. Here, we have presented edge detection in the preprocessing stage. It is important that the edge detector should give the character edges without fragmentation and displacement of edge pixels. Canny edge detector is used to produce thinned edges of the character. But for high resolution images, it gives spurious branches corresponding to noise and texture of the image. So a technique is applied prior to this process to focus the edge regions using nonlinear an isotropic diffusion via partial differential equations (PDE). Even though this method helped to get accurate edge points, the final result shows some broken edges. These broken parts are then linked using ant colony optimization (ACO) method. This image is further partitioned into different zones for the purpose of feature extraction. Multi layer perceptron (MLP) used these features and classified the characters with a recognition accuracy of 95.16%.