Abstract

The detection and recognition of text in a scene image is a very challenging problem in image processing because of the high complexity of background in the image. The acquired image is pre-processed by the YUV channel conversion technique and the Y channel image is converted to a gray scale image. Connected Component Based Text Segmentation Algorithm (CCBTSA) and MSER methods are used for segmentation and recognition of text using Optical Character Recognition (OCR). GLCM and FOS features are extracted from the segmented region. Segmented text character is used to extract by using Template matching algorithm. Performances are analysed based on the recall rate, precision, accuracy and F-measure. From the experimental effects, the accuracy of the SVM classifier was gained as 96.7%.

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