Feature Based Binarization of Document Images Degraded by Uneven Light Condition

This paper proposes a document image binarization method, which is especially robust to the images degraded by uneven light condition, such as the camera captured document images. A descriptor that captures the regional properties around a given pixel is first defined for this purpose. For each pixel, the descriptor is defined as a vector composed of filter responses with varying length. This descriptor is shown to give highly discriminating pattern with respect to the background region, text region, and near text region. Of course there are misclassified pixels, which are then relabeled using an energy optimization methodbased on graph cut method. For this, we devise an appropriate energy function that leads to clear and correct binarization. The proposed descriptor is also used for the skew detection, and thus correcting the skewed documents.

• Type: Conference
• Year: 2009
• Where: ICDAR
• Authors: Jung Gap Kuk, Nam Ik Cho
• Keywords: Document Analysis, Document Images, ICDAR 2009, Text Region, Uneven Light Condition