Abstract
In this paper, a robust technique for identifying and recognizing Handwritten Text images is presented. There are many methods for Handwritten Text, but most of them require segmentation or connected component analysis. The Recognition process utilizes the determinant value that produces the features for the Handwritten Text. Image's determinants values are computed by dividing image into blocks then designed Threshold (T) to extract feature, afterwards, use chain code to find the centric point and direction of text. The least square criterion is then utilized to determine the similarity between the existed (in Database file) Handwritten Text with a new query Handwritten Text's images.
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