A method of color image edge extraction based on Manhattan distance map

Author

Di Jia ; Jin-feng Fang ; Xue-ping He ; Lu Meng ; Yi-fei Zhang

Author_Institution

Sch. of Electron. & Inf. Eng., LiaoNing Tech. Univ., Huludao, China

fYear

2013

fDate

23-25 July 2013

Firstpage

990

Lastpage

994

Abstract

Edge extraction is an important topic of image processing, and it is also the basis for subsequent processing. For this reason, this paper proposed a method of color image edge extraction based on Manhattan distance map. Firstly, Manhattan distance map is constructed by adjusting the fuzzy radius and the standard deviation of Gauss nuclear. Edge of the image will be enhanced through the Manhattan distance map, and the gray value of "background" will be reduced. Secondly, Edge of the area is extracted by analysis the gray distribution features of distance map through threshold, and edge region is constructed by the area of edge as foundation. Because the edge region has continuous characteristic, it can be used as the initial distance matrix for GAC model. Finally, edges will be extracted by iterative GAC model in the original image. The results show the method has a better accuracy and practicability.

Keywords

Gaussian processes; edge detection; feature extraction; fuzzy set theory; image colour analysis; image segmentation; iterative methods; Gauss nuclear standard deviation; Manhattan distance map; background gray value; color image edge extraction method; edge region; fuzzy radius; gray distribution features; image processing; iterative GAC model; Accuracy; Color; Feature extraction; Image color analysis; Image edge detection; Image segmentation; Mathematical model; GAC model; Gauss template; Manhattan distance map; Segmentation threshold; edge extracting;

fLanguage

English

Publisher

ieee

Conference_Titel

Natural Computation (ICNC), 2013 Ninth International Conference on

Conference_Location

Shenyang

Type

conf

DOI

10.1109/ICNC.2013.6818120

Filename

6818120