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Adaptive document block segmentation and classification.

F Y Shih¹, S S Chen

¹Comput. Vision Lab., New Jersey Inst. of Technol., Newark, NJ.

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society

|January 1, 1996

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This study introduces an adaptive technique for segmenting and classifying office documents. The method accurately processes complex layouts with text, graphics, and pictures, improving document analysis.

Area of Science:

Computer Science
Document Image Analysis

Background:

Office documents often feature complex layouts with mixed content like text, graphics, and images.
Accurate segmentation and classification are crucial for automated document processing.

Purpose of the Study:

To present an adaptive block segmentation and classification technique for complex office documents.
To develop a method robust to variations in font, size, and scanning resolution.

Main Methods:

Employs an improved two-step block segmentation algorithm using run-length smoothing.
Utilizes a rule-based classification system to categorize blocks into text, lines, graphics, or pictures.

Main Results:

The technique successfully decomposes documents into single-mode blocks.

Related Experiment Videos

Experimental results demonstrate accurate segmentation and classification of diverse mixed-mode documents.

Conclusions:

The proposed adaptive technique effectively handles complex document layouts.
The method offers a robust solution for automated analysis of office documents.