Pattern Recognition
Image enhancement and thresholding by optimization of fuzzy compactness
Pattern Recognition Letters
Automatic thresholding of gray-level pictures using two-dimensional entropy
Computer Vision, Graphics, and Image Processing
Goal-Directed Evaluation of Binarization Methods
IEEE Transactions on Pattern Analysis and Machine Intelligence
Mathematical properties of the native integral ratio handwriting and text extraction technique
ICDAR '97 Proceedings of the 4th International Conference on Document Analysis and Recognition
Automatic Thresholding of Gray-level Using Multi-stage Approach
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
Input sensitive thresholding for ancient Hebrew manuscript
Pattern Recognition Letters
Card Images Binarization Based on Dual-Thresholding Identification
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence
A multi-plane approach for text segmentation of complex document images
Pattern Recognition
A fast estimation method for the generalized Gaussian mixture distribution on complex images
Computer Vision and Image Understanding
A binarization algorithm for historical manuscripts
ICCOM'08 Proceedings of the 12th WSEAS international conference on Communications
Gray level difference-based transition region extraction and thresholding
Computers and Electrical Engineering
Modified local entropy-based transition region extraction and thresholding
Applied Soft Computing
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In this paper, we propose a new class of histogram based global thresholding techniques called Integral Ratio. They are designed to threshold gray-scale handwriting images and separate the handwriting from the background. The following tight requirements must be met: 1) all the details of the handwriting are to be retained, 2) the writing paper used may contain strong colored and/or patterned background which must be removed, and 3) the handwriting may be written using a wide variety of pens such as a fountain pen, ballpoint pen, or pencil. A specific application area which requires these tight requirements is forensic document examination, where a handwritten document is often considered as legal evidence and the handwriting must not be tampered with or modified in any way. The proposed class of techniques is based on a two stage thresholding approach requiring each pixel of a handwritten image to be placed into one of three classes: foreground, background, and a fuzzy area between them where it is hard to determine whether a pixel belongs to the foreground or the background. Two techniques, Native Integral Ratio (NIR) and Quadratic Integral Ratio (QIR), were created based on this class and tested against two well-known thresholding techniques: Otsu's technique and the Entropy thresholding technique. We found that QIR has superior performance compared to all the other techniques tested.