Extraction of Text Region From Color Image Sequence of A Book Cover Containing Gilt Characters

Yang, Hua; Ozawa, Shogo

doi:10.1541/ieejeiss1987.122.4_630

Cited by 3 publications

(1 citation statement)

References 3 publications

(1 reference statement)

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“…There has been extensive research on the extraction of characters from images [12][13][14][15][16][17]. Characters and drawings include much information on geometric shapes rather than density.…”

Section: Application To Character Extractionmentioning

confidence: 99%

Thresholding algorithm for local and parallel processing

Iwakata

Ajioka²,

Hagiwara

2006

Electrical Engineering Japan

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SUMMARYIn this paper, we propose a thresholding algorithm. This algorithm works under a severe constraint: each pixel in a processed image must be derived from only information of its neighboring pixels. This constraint is very important for a low-cost device such as a mobile camera, because it makes it possible to process each pixel in parallel. The proposed algorithm deals with gray-scale images, and determines the threshold based on edge information. The proposed algorithm is represented by local and parallel image processing and has been tested using 104 scenery images. The result shows that the proposed algorithm can binarize images.

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Section: Application To Character Extractionmentioning

confidence: 99%

Thresholding algorithm for local and parallel processing

Iwakata

Ajioka²,

Hagiwara

2006

Electrical Engineering Japan

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Thresholds decision method for fast object detection systems

Satō

Mitsukura

Fukumi

et al.

Proceedings 2003 IEEE International Symposium on Computational Intelligence in Robotics and Automation. Computational Intellige

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In this paper, we propose a new determination method of color thresholds for extracting objects. In order to obtain the optimal color threshold, it is necessary to determine RGB values all together because one color consists of a combination of RGB values. The two optimal thresholds, a upper and a lower, are determined for object extraction by applying genetic algorithm. Moreover, in the proposed method, individuals are evaluated using two fitness functions for obtaining the optimal color thresholds, and initial population is generated with color histograms for fast convergence. Finally, computer simulations are performed, and the result images are shown.image processing, object extraction, threshold, genetic algorithm, fitness function 0-7803-7866-0/03/$17.00 02003 IEEE

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Thresholding Algorithm for Local and Parallel Processing

Iwakata

Ajioka²,

Hagiwara

2005

IEEJ Trans.EIS

View full text Add to dashboard Cite

In this paper, we propose a thresholding algorithm. This algorithm works under a severe constraint: each pixel in a processed image must be derived from only information of its neighboring pixels. This constraint is very important for a low cost device such as a mobile camera, because it makes possible to process each pixel in parallel. The proposed algorithm deals with gray-scale images, and determines the threshold based on edge information. The proposed algorithm is represented by local and parallel image processing and has been tested using 104 scenery images. The result shows that the proposed algorithm can binarizing images.

show abstract

Extraction of Text Region From Color Image Sequence of A Book Cover Containing Gilt Characters

Cited by 3 publications

References 3 publications

Thresholding algorithm for local and parallel processing

Thresholding algorithm for local and parallel processing

Thresholds decision method for fast object detection systems

Thresholding Algorithm for Local and Parallel Processing

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