A Hybrid Approach to Localize Farsi Text in Natural Scene Images

Text in scene images can provide useful and vital information for content-based image analysis. Therefore, localization of text in images is an important task. In this paper, we present a hybrid approach to localize Farsi text in natural scene images. Complex background, variations of text font, size and line orientation and non-uniform illumination are the problems of this method. The Language of text localization in the past works is almost limited to English or Chinese. In this paper we consider Farsi/Arabic language for text localization. Due to the specific features of this language challenges of text localization are numerous. In this paper, in the first step a new color based method is proposed for extracting candidate regions, then the texts in natural scene images are detected by combining edge and color features. Variation due to text size and orientation, are resolved by a new pyramid of images. The candidate texts are verified by combination of two features, wavelet histogram and histogram of oriented gradient. Experimental results using our large dataset have demonstrated that the proposed method is effective and promising.