Abstract

Text in natural scene images may provide important information based on the application. Detecting text from natural scene should be effective; for that, segmenting text from natural scene images should use a high-performance method. In this paper, an efficient segmentation and classification technique is used. Given system takes natural scene images as input. After converting the color image to grayscale image, histogram of oriented gradients (HOG) features is used to find the edge values. Image is segmented using Ni-Black local binarization, which identifies the edge on suppressing image’s background. Image is classified using CRF which blocks the text in the natural scene images. This system provides better segmentation of text and classifies with high detection accuracy.

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