Abstract
Text location and recognition is a vital and fundamental problem of processing images. In this paper we propose a novel system for text location and recognition focused on book covers. Our work consists of two main parts, learning-based text location and adaptive binarization guided recognition. First we extract three types of robust features from the training data provided on ICDAR2005 and utilize Ada-boost to combine these features into a powerful classifier for text regions detection and location. Second we apply the proposed adaptive binarization to process the located regions for recognition. Compared with previous works, our algorithm is robust in size, font and color of text, and insensitive for languages. In experiments, our system proved to have attractive performance.
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