Please use this identifier to cite or link to this item:
Title: Image Segmentation Using Thresholding and Genetic Algorithm
Authors: Kanungo, P
Nanda, P K
Samal, U C
Keywords: Segmentation
Genetic Algorithms
Issue Date: 2006
Publisher: NIT, Rourkela, India
Citation: Proceedings of the Conference on Soft Computing Technique for Engineering Applications, SCT 2006, March 24-26, 2006, Rourkela, India
Abstract: In this paper the problem of image segmentation is addressed using the notion of thresholding. A new approach based on Genetic Algorithm (GA) is proposed for selection of threshold from the histogram of images. Specifically GA based crowding algorithm is proposed for determination of the peaks and valleys of the histogram. Experimental results are provided for histogram with bimodal feature, however, this technique can be extended to multi threshold selection for histograms with multimodal feature.
Description: Copyright for this article belongs to National Institute of Technology, Rourkela
Appears in Collections:Conference Papers

Files in This Item:
File Description SizeFormat 
Pkanungo_Pknanda_Usamal_SCT20061.pdf487.75 kBAdobe PDFView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.