Pattern Recognition
An Iterative Thresholding Algorithm for Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Algorithms for clustering data
Algorithms for clustering data
A survey of thresholding techniques
Computer Vision, Graphics, and Image Processing
A Spatial Thresholding Method for Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Evaluation of Binarization Methods for Document Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Game-Theoretic Integration for Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image Thresholding by Indicator Kriging
IEEE Transactions on Pattern Analysis and Machine Intelligence
Twenty Years of Document Image Analysis in PAMI
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognizing Characters in Scene Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Goal-Directed Evaluation of Binarization Methods
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multi-scale binarization of images
Pattern Recognition Letters
An Integrated Approach for Surface Finding in Medical Images
MMBIA '96 Proceedings of the 1996 Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA '96)
Using connected components to guide image understanding and segmentation
Machine Graphics & Vision International Journal
Optimal combination of document binarization techniques using a self-organizing map neural network
Engineering Applications of Artificial Intelligence
Estimation of proper parameter values for document binarization
CGIM '08 Proceedings of the Tenth IASTED International Conference on Computer Graphics and Imaging
Novel classification and segmentation techniques with application to remotely sensed images
Transactions on rough sets VII
A document binarization method based on connected operators
Pattern Recognition Letters
Crack detection in X-ray images using fuzzy index measure
Applied Soft Computing
A new binarization method for non-uniform illuminated document images
Pattern Recognition
Historical document image restoration using multispectral imaging system
Pattern Recognition
| Hi-index | 0.14 |
Several methods for segmentation of document images (maps, drawings, etc.) are explored. The segmentation operation is posed as a statistical classification task with two pattern classes: print and background. A number of classification strategies are available. All require some prior information about the distribution of gray levels for the two classes. Training (either supervised or unsupervised) is employed to form these initial density estimates. Automatic updating of the class-conditional densities is performed within subregions in the image to adapt these global density estimates to the local image area. After local class-conditional densities have been obtained, each pixel is classified within the window using several techniques: a noncontextual Bayes classifier, Besag's classifier, relaxation, Owen and Switzer's classifier, and Haslett's classifier. Four test images were processed. In two of these, the relaxation method performed best, and in the other two, the noncontextual method performed best. Automatic updating improved the results for both classifiers.