Image Normalization and Preprocessing for Gujarati Character Recognition

Pattern recognition has been an important area in computer vision applications. In the case of a planar image, there are four basic forms of geometric distortion caused by the change in camera location: translation, rotation, scaling and skew. So far, a number of methods have been developed to solve these distortions, such as moment invariants’, Fourier descriptor, Hough transformation, shape matrix’ and the principle axis method. All of the above methods can be made invariant to translation, rotation and scaling. However, they become useless when pattern is skewed: when the direction of the camera or scanner is not vertical to the planar image or the sampling intervals in the x and y directions are not equal, the image is skewed. Authors present a moment based normalization process for character images for the purpose of enhancing the performance of character recognize for isolated characters of Gujarati. This paper focuses on character pre-processing and normalization stage of handwritten character recognition for Gujarati