Hierarchical Image Analysis Using Irregular Tessellations
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Survey of Methods and Strategies in Character Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Twenty Years of Document Image Analysis in PAMI
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic Separation of Words in Multi-lingual Multi-script Indian Documents
ICDAR '97 Proceedings of the 4th International Conference on Document Analysis and Recognition
Character Extraction from Noisy Background for an Automatic Reference System
ICDAR '99 Proceedings of the Fifth International Conference on Document Analysis and Recognition
Segmenting Document Images Using Diagonal White Runs and Vertical Edges
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Detection of Word Groups Based on Irregular Pyramid
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Statistical-Based Approach to Word Segmentation
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 4
IBM Journal of Research and Development
Multi-oriented Bangla and Devnagari text recognition
Pattern Recognition
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This paper presents the result of our continued work on a further enhancement to our previous proposed algorithm. Moving beyond the extraction of word groups and based on the same irregular pyramid structure the new proposed algorithm groups the extracted words into sentences. The uniqueness of the algorithm is in its ability to process text of a wide variation in terms of size, font, orientation and layout on the same document image. No assumption is made on any specified document type. The algorithm is based on the irregular pyramid structure with the application of four fundamental concepts. The first is the inclusion of background information. The second is the concept of closeness where text information within a group is close to each other, in terms of spatial distance, as compared to other text areas. The third is the "majority win" strategy that is more suitable under the greatly varying environment than a constant threshold value. The final concept is the uniformity and continuity among words belonging to the same sentence.