Applying preattentive visual guidance in document image analysis

Authors:
Di Wen;Xiaoqing Ding
Affiliations:
Department of Electronic Engineering, Tsinghua University;Department of Electronic Engineering, Tsinghua University
Venue:
IWICPAS'06 Proceedings of the 2006 Advances in Machine Vision, Image Processing, and Pattern Analysis international conference on Intelligent Computing in Pattern Analysis/Synthesis
Year:
2006

Citing 15
Cited 0

A Prototype Document Image Analysis System for Technical Journals

Computer
Text segmentation using Gabor filters for automatic document processing

Machine Vision and Applications - Special issue: document image analysis techniques
Pyramid-based texture analysis/synthesis

SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
High-speed visual estimation using preattentive processing

ACM Transactions on Computer-Human Interaction (TOCHI)
A simplified approach to the HMM based texture analysis and its application to document segmentation

Pattern Recognition Letters
Filters, Random Fields and Maximum Entropy (FRAME): Towards a Unified Theory for Texture Modeling

International Journal of Computer Vision
A Model of Saliency-Based Visual Attention for Rapid Scene Analysis

IEEE Transactions on Pattern Analysis and Machine Intelligence
An Optimization Methodology for Document Structure Extraction on Latin Character Documents

IEEE Transactions on Pattern Analysis and Machine Intelligence
Page segmentation and classification utilising a bottom-up approach

ICDAR '95 Proceedings of the Third International Conference on Document Analysis and Recognition (Volume 2) - Volume 2
Visual similarity based document layout analysis

Journal of Computer Science and Technology - Special section on China AVS standard
Minimax Entropy Principle and Its Application to Texture Modeling

Neural Computation
Document analysis system

IBM Journal of Research and Development
Page segmentation using texture analysis

Pattern Recognition
Context-based multiscale classification of document images using wavelet coefficient distributions

IEEE Transactions on Image Processing
Texture classification using spectral histograms

IEEE Transactions on Image Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we present a novel methodology on document image analysis (DIA) which harnesses the mechanism of preattentive visual guidance in human vision. Summarizing the psychophysical discoveries on preattentive vision, we propose two types of computational simulations of this biological process: the visual similarity clustering and visual saliency detection, based on which we implement a novel biological plausible way to guide the interpretation of document images. Experimental results prove the efficiency of these two computational processes, whose outputs can be further utilized by other task-oriented DIA applications.