A Hybrid Method for Historical Degraded Document Image

This paper addresses the problem of document image binarization, in which we present a new binarization method based on the use of a supervised learning support vector machine SVM, that accurately segment the text in the degraded document image. First we start by enhance the contrast of the original image. Then, a feature selection is making by using an inpainting algorithm. The last phase is the use of support vector machine to classify the pixels of the original image into "1" or "0" to construct the binary image. The suggested method has been tested and evaluated over the benchmarking in the document binarization: DIBCO'2009.

• document image binarization
• degraded document images
• text segmentation
• support vector machine
• image inpainting
• feature selection
• contrast enhancement

• Handwritten Text Recognition Techniques
• Image Processing and 3D Reconstruction
• Vehicle License Plate Recognition
• document image binarization
• degraded document images
• text segmentation
• support vector machine
• image inpainting
• feature selection
• contrast enhancement
• Computer Vision and Pattern Recognition
• Media Technology
• Computer Science
• Engineering