Text detection and recognition in natural scene images

Text detection in natural scenes is an important but challenging problem because of variations in the text fonts, size, line orientation, complex background in image and non-uniform illuminations. To overcome these problems, effective features for text image recognition are used.In this paper, a text region detector is designed by using a widely used feature descriptor, histogram of oriented gradients (HOG). Local binarization is applied to segment connected components. For text extraction, parameters like normalized height width ratio and compactness are taken into account to filter out text and non-text components. Text recognition is implemented using zone centroid and image centroid based distance metric feature extraction system.