A fast 2D entropic thresholding method by wavelet decomposition

Qing Wang; Qiurang Wang; David Dagan Feng; Rongchun Zhao; Zheru Chi

A fast 2D entropic thresholding method by wavelet decomposition

Qing Wang, Qiurang Wang, David Dagan Feng, Rongchun Zhao, Zheru Chi

The Hong Kong Polytechnic University

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

4 Citations (Scopus)

Abstract

Compare with 1D grayscale histogram analysis, 2D entropic thresholding makes use of local average as well as pixel gray level. However, it is time consuming to search the threshold vector in 2D histogram. In the paper, a fast algorithm using wavelet decomposition is proposed, with which a set of candidates of vector was first obtained in the decomposed histogram. The optimal threshold vector is then obtained without exhaustive searching. Experimental results have shown that our algorithm not only find the threshold vector as same as Brink's method but also save computation costs in a large degree, using up only 0.53% of processing time taken by the exhaustive searching.

Original language	English
Title of host publication	IEEE International Conference on Image Processing
Publication status	Published - 1 Jan 2002
Event	International Conference on Image Processing (ICIP'02) - Rochester, NY, United States Duration: 22 Sept 2002 → 25 Sept 2002

Conference

Conference	International Conference on Image Processing (ICIP'02)
Country/Territory	United States
City	Rochester, NY
Period	22/09/02 → 25/09/02

ASJC Scopus subject areas

Hardware and Architecture
Computer Vision and Pattern Recognition
Electrical and Electronic Engineering

Cite this

@inproceedings{e30f341638db4a44b3de29c9ad3193c0,

title = "A fast 2D entropic thresholding method by wavelet decomposition",

abstract = "Compare with 1D grayscale histogram analysis, 2D entropic thresholding makes use of local average as well as pixel gray level. However, it is time consuming to search the threshold vector in 2D histogram. In the paper, a fast algorithm using wavelet decomposition is proposed, with which a set of candidates of vector was first obtained in the decomposed histogram. The optimal threshold vector is then obtained without exhaustive searching. Experimental results have shown that our algorithm not only find the threshold vector as same as Brink's method but also save computation costs in a large degree, using up only 0.53% of processing time taken by the exhaustive searching.",

author = "Qing Wang and Qiurang Wang and Feng, {David Dagan} and Rongchun Zhao and Zheru Chi",

year = "2002",

month = jan,

day = "1",

language = "English",

booktitle = "IEEE International Conference on Image Processing",

note = "International Conference on Image Processing (ICIP'02) ; Conference date: 22-09-2002 Through 25-09-2002",

}

TY - GEN

T1 - A fast 2D entropic thresholding method by wavelet decomposition

AU - Wang, Qing

AU - Wang, Qiurang

AU - Feng, David Dagan

AU - Zhao, Rongchun

AU - Chi, Zheru

PY - 2002/1/1

Y1 - 2002/1/1

N2 - Compare with 1D grayscale histogram analysis, 2D entropic thresholding makes use of local average as well as pixel gray level. However, it is time consuming to search the threshold vector in 2D histogram. In the paper, a fast algorithm using wavelet decomposition is proposed, with which a set of candidates of vector was first obtained in the decomposed histogram. The optimal threshold vector is then obtained without exhaustive searching. Experimental results have shown that our algorithm not only find the threshold vector as same as Brink's method but also save computation costs in a large degree, using up only 0.53% of processing time taken by the exhaustive searching.

AB - Compare with 1D grayscale histogram analysis, 2D entropic thresholding makes use of local average as well as pixel gray level. However, it is time consuming to search the threshold vector in 2D histogram. In the paper, a fast algorithm using wavelet decomposition is proposed, with which a set of candidates of vector was first obtained in the decomposed histogram. The optimal threshold vector is then obtained without exhaustive searching. Experimental results have shown that our algorithm not only find the threshold vector as same as Brink's method but also save computation costs in a large degree, using up only 0.53% of processing time taken by the exhaustive searching.

UR - http://www.scopus.com/inward/record.url?scp=0036452704&partnerID=8YFLogxK

M3 - Conference article published in proceeding or book

BT - IEEE International Conference on Image Processing

T2 - International Conference on Image Processing (ICIP'02)

Y2 - 22 September 2002 through 25 September 2002

ER -

A fast 2D entropic thresholding method by wavelet decomposition

Abstract

Conference

ASJC Scopus subject areas

Other files and links

Fingerprint

Cite this