Odia Compound Character Recognition Using Stroke Analysis

In Odia optical character recognition (OCR) model, detection of compound characters plays a very important role. The 80% of allograph classes present in Odia script is compound. Here a zone-based stroke analysis model is used to recognize the compound characters. Each character is divided into nine zones, and each zone has some similarity to one or few of the considered 12 strokes. For similarity measure, structural similarity index (SSIM) is used. This proposed feature have a higher potential for recognizing compound characters. The recognition accuracy of 92% is obtained for characters in Kalinga font.