Image thresholding using differential evolution

Shahryar Rahnamayan, Hamid R. Tizhoosh, Magdy M.A. Salama

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Image thresholding is a challenging task in image processing field. Many efforts have already been made to propose universal, robust methods to handle a wide range of images. This paper introduces a new optimization-based thresholding approach. The optimizer, Differential Evolution (DE) algorithm, minimizes dissimilarity between the input grey-level image and the bi-level (thresholded) image. The proposed approach is compared with a well-known thresholding method, Kittler algorithm, through subjective and objective assessments, and experimental results are provided.

Original languageEnglish (US)
Title of host publicationProceedings of the 2006 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV'06
Pages244-249
Number of pages6
StatePublished - 2006
Event2006 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV'06 - Las Vegas, NV, United States
Duration: Jun 26 2006Jun 29 2006

Publication series

NameProceedings of the 2006 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV'06
Volume1

Conference

Conference2006 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV'06
Country/TerritoryUnited States
CityLas Vegas, NV
Period6/26/066/29/06

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