Local Binary Pattern-Based Features for Text Identification of Web Images

We present a method of robustly identifying a text block in complex web images. The method is a MLP (Multi-layer perceptron) classifier trained on LBP (Local binary patterns), wavelet and shape feature spaces. Especially, we propose adaptive masks of LBP which responses flexibly to various character sizes. Most of previous works use fixed mask size or multi level scales by pyramid schemes, which may have weakness in dealing with diverse size of text. Experiments carried out on 100 web images show promising results.