Unified approach for document segmentation

Horacio Andrés Legal-Ayala; Jacques Facon

doi:10.1117/12.591675

21 October 2004 Unified approach for document segmentation

Horacio Andrés Legal-Ayala, Jacques Facon

Proceedings Volume 5622, 5th Iberoamerican Meeting on Optics and 8th Latin American Meeting on Optics, Lasers, and Their Applications; (2004) https://doi.org/10.1117/12.591675
Event: 5th Iberoamerican Meeting on Optics and 8th Latin American Meeting on Optics, Lasers, and Their Applications, 2004, Porlamar, Venezuela

Abstract

In this paper, we propose a unified approach for document segmentation. Differently of others techniques that segment images without a priori knowledge about the classes to be segmented, this approach carries out a previous learning of what must be segmented. The learning is carried out using only two images, the original one and its ideal segmented version. This stage generates a decision matrix, which is used to extract the similar semantic information in new images. The knowledge acquired in the decision matrix is explored by means of KNN strategy. Performed tests on different types of document images, like signature, postal envelopes and old document databases for instance, showed significant and promising results. It must be emphasized that this learning segmentation approach is completely automatic, does not require heuristics, and may transform the subjective human operator's knowledge into an automatic process and reproduce it.

Citation Download Citation

Horacio Andrés Legal-Ayala and Jacques Facon "Unified approach for document segmentation", Proc. SPIE 5622, 5th Iberoamerican Meeting on Optics and 8th Latin American Meeting on Optics, Lasers, and Their Applications, (21 October 2004); https://doi.org/10.1117/12.591675

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KEYWORDS

Image segmentation

Databases

Image processing

Binary data

Genetic algorithms

Neural networks

Feature selection

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