Thresholding Algorithm for Local and Parallel Processing

Satohi Iwakata; Masafumi Hagiwara; Yoshiaki Ajioka

doi:10.1541/ieejeiss.125.7

Thresholding Algorithm for Local and Parallel Processing

Satohi Iwakata, Masafumi Hagiwara, Yoshiaki Ajioka

Department of Information and Computer Science

Research output: Contribution to journal › Article › peer-review

4 Citations (Scopus)

Abstract

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.

Original language	English
Pages (from-to)	7-13
Number of pages	7
Journal	IEEJ Transactions on Electronics, Information and Systems
Volume	125
Issue number	1
DOIs	https://doi.org/10.1541/ieejeiss.125.7
Publication status	Published - 2005 Jan

Keywords

character extraction
image processing
local and parallel image processing
scenery image
support for sight-restricted people
thresholding

ASJC Scopus subject areas

Electrical and Electronic Engineering

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10.1541/ieejeiss.125.7

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AU - Hagiwara, Masafumi

AU - Ajioka, Yoshiaki

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AB - 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.

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KW - image processing

KW - local and parallel image processing

KW - scenery image

KW - support for sight-restricted people

KW - thresholding

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Thresholding Algorithm for Local and Parallel Processing

Abstract

Keywords

ASJC Scopus subject areas

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