An Efficient Method of Text Localization in Complicated Background Scenes

Abstract

We propose a novel method for text localization in low illumination images with complicated background scenes. Low illumination image, complex background and variations of text script make text localization problem challenging. The proposed method use density-based information and rectangle window in the residual edge image. The proposed method firstly is color space conversion from RGB to Ycbcr color space, secondly we extract Y component from Ycbcr color space and get image enhancement from Y component, then extract out the vertical edges of enhanced Y component, thirdly, long curve and random noise in complicated background are removed, finally, search the text localization and segment the text out from the original low illumination images. We evaluate our method using natural image data set and ICDAR data set. The experimental results show that the proposed method has more robust to interference characters and more accurate when compared with other methods.