Empirical Performance Evaluation of Graphics Recognition Systems
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computer Vision
Page segmentation and classification using fast feature extraction and connectivity analysis
ICDAR '95 Proceedings of the Third International Conference on Document Analysis and Recognition (Volume 2) - Volume 2
Structured Document Segmentation and Representation by the Modified X-Y tree
ICDAR '99 Proceedings of the Fifth International Conference on Document Analysis and Recognition
ICDAR '07 Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 02
Audio-adaptive animation from still image
Transactions on Computational Science XIX
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A bottom-up approach to segmentation of a scanned document into background, text, and image regions is considered. The image is partitioned into blocks at the first step. A series of texture features is computed for each block. The block type is determined on the basis of these features. Different variants of block arrangement and size, 26 texture variables, and four block type classification algorithms have been considered. The block type is corrected on the basis of adjacent region analysis at the second step. The error matrix and ICDAR 2007 criterion are used for result estimation.