The Study of Feature Extraction Based on the Optimal Threshold Segmentation Algorithm

Xia Ren; Lian Xiang Ma

doi:10.4028/www.scientific.net/KEM.561.652

Paper Titles

The Design of Workpiece Hydraulic Clamping System of a Special CNC Machine Tool for Guide Disc
p.630

Test Research for Thermal Protective Properties of Mobile Refuge Chamber
p.635

Terahertz Time-Domain Spectroscopy Technology and its Application in the Field of Pesticide
p.640

The Research Progress on Pressure Drop of Rotating Packed Bed
p.646

The Study of Feature Extraction Based on the Optimal Threshold Segmentation Algorithm
p.652

Numerical Analysis for Thermal-Chemical-Stress Coupling in Deep Rock Creep Properties
p.657

Design of Open-Architecture Gantry Milling NC System Based on Motion Control Card
p.663

The Tank Bottom Safety Detection Based on Acoustic Emission Technology
p.667

Numerical Simulation of Counter-Current Flow Field in Double Packing Rotating Packed Bed
p.672

HomeKey Engineering MaterialsKey Engineering Materials Vol. 561The Study of Feature Extraction Based on the...

The Study of Feature Extraction Based on the Optimal Threshold Segmentation Algorithm

Abstract:

Image segmentation technology is crucial for feature extraction. In this paper, the traditional thresholding method has been improved, and the optimal threshold segmentation method is proposed by combining the iterative algorithm and mathematical morphology. Through analyzing the target area of image, the scope of the general gray-scale is determined. Based on the image edge and region, fast iterative algorithm is used to choose the optimum threshold as segmentation criteria. Moreover, morphology open computing is applied to the image threshold segmentation. Then the method is used in processing marine oil spill and solar flares. Different experiments of marine oil spill and solar flares based on the method show that this method can not only extract a clearer definition of interesting areas, but also can show a more clear-cut edge.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Key Engineering Materials (Volume 561)

Pages:

652-656

DOI:

https://doi.org/10.4028/www.scientific.net/KEM.561.652

Citation:

Cite this paper

Online since:

July 2013

Authors:

Xia Ren, Lian Xiang Ma

Keywords:

Iterative Algorithm, Mage Segmentation, Mathematical Morphology, Optimal Threshold

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] HAN Si-qi,WANG Lei. Image Segmentation Summary of the threshold law[J]. Systems Engineering and Electronic Technology, 2002, 4(6): 91-102

Google Scholar

[2] Y J Zhang. A survey on evaluation methods for image segmentation [J]．Pattern Recognition．1996，29(8)：1335-1346

Google Scholar

[3] ZHAO Chun-yan, YAN Chang-qing, SHI Xiu-fang. Summary of Image Segmentation[J].China Science And Technology Information. 2009, 1: 42-43

Google Scholar

[4] LI Hua-qiang, YU Qing-cang, FANG Mei. Application of Otsu Thresholding method on Canny operator[J].Computer Engineering and Design,2008,29(9):2297-2298

Google Scholar

[5] WANG Yong-bo, CHEN Ji-rong. Improvement of Two-dimensional Otsu Algorithm and Its Application[J].Computer Simulation, 2008, 25(4): 263-266

Google Scholar

[6] ZHAO Jun-mei, ZHANG Li-ping. A Method of Vehicle License Recognition Based on Mathematical Morphology[J].Vehicle & Power Technology,2008,4:31-34

Google Scholar

[7] ZHANG Sha-sha. Image Segmentation and Tracking Algorithm for Moving Target[J]. Computer Application, 2006, 2-4, 34-42

Google Scholar