Camera Captured Kannada Hand-Written Document Binarization & Segmentation in Color Space
Vinod H C1, S K Niranjan2
1Vinod H C, Department of Information Science and Engineering, SJB Institute of Technology, Bangalore, India.
2S K Niranjan, Department of Computer Applications, JSS Science and Technology University, Mysuru, India.
Manuscript received on 02 June 2019 | Revised Manuscript received on 10 June 2019 | Manuscript published on 30 June 2019 | PP: 1208-1213 | Volume-8 Issue-8, June 2019 | Retrieval Number: H6931068819/19©BEIESP
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Abstract: Binarization of document images is a major phase in the handwritten text recognition process. Text recognition process gives best result and easy to archive recognition for printed documents, but more accurate and fast Binarization & segmentation methods are required to achieve high accuracy in handwritten character recognition. In this paper we presenting Document Binarization & Segmentation. In Document Binarization initially we convert RGB color space image to CMY color space further calculate the average of C, M & Y. Finally convert the grey scale image to binary by determining threshold value automatically. Segmentation is done by the projection profile method and paragraph skew correction recursively until height of the segmented line image is less than 7% of the input image, Connected Component Analysis is used to segment words. These segmented words can be feed to OCR for recognition; the proposed experimental results are encouraging.
Keyword: CMY Color Space, Connected Component Analysis, Projection Profile, RGB Color Space.
Scope of the Article: Image analysis and Processing.