New Wavelet and Color Features for Text Detection in Video

Automatic text detection in video is an important task for efficient and accurate indexing and retrieval of multimedia data such as events identification, events boundary identification etc. This paper presents a new method comprising of wavelet decomposition and color features namely R, G and B. The wavelet decomposition is applied on three color bands separately to obtain three high frequency sub bands (LH, HL and HH) and then the average of the three sub bands for each color band is computed further to enhance the text pixels in video frame. To take advantage of wavelet and color information, we again take the average of the three average images (AoA) obtained by the former step to increase the gap between text and non text pixels. Our previous Laplacian method is employed on AoA for text detection. The proposed method is evaluated by testing on a large dataset which includes publicly available data, non text data and ICDAR-03 data. Comparative study with existing methods shows that the results of the proposed method are encouraging and useful.