An improved method for edge detection based on interval type-2 fuzzy logic

被引：158

作者：

Melin, Patricia ^{[1
]}

Mendoza, Olivia ^{[2
]}

Castillo, Oscar ^{[1
]}

机构：

[1] Tijuana Inst Technol, Dept Res & Grad Studies, Chula Vista, CA USA

[2] Univ Baja California, Sch Engn, Tijuana, Mexico

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2010年 / 37卷 / 12期

关键词：

Digital images; Edge detection; Image processing; Interval type-2 fuzzy logic;

D O I：

10.1016/j.eswa.2010.05.023

中图分类号：

TP18 [人工智能理论];

学科分类号：

140502 [人工智能];

摘要：

In this paper, a method for edge detection in digital images based on the morphological gradient and fuzzy logic is described. A basic method for edge detection was improved using fuzzy logic. An advantage of the improved method is that there is no need of applying filtering to the image. The simulation results were obtained with a type-1 fuzzy inference system (T1FIS) and with an interval type-2 fuzzy inference system (IT2FIS) for improving the edge detection method. We show that the images obtained with fuzzy logic are better than the ones obtained with only the morphological gradient method. In particular the IT2FIS achieved the best results, because of the flexibility to model the uncertainty in the gradient values and the gray ranges for the edge images. In both T1FIS and IT2FIS the membership function parameters were obtained directly from the images: this allows application of the proposed method to images with different gray scales. (C) 2010 Elsevier Ltd. All rights reserved.

引用

页码：8527 / 8535

页数：9

共 21 条

[1]

[Anonymous], ORL DAT FAC

[2]

[Anonymous], USC SIPI IM DAT

[3]

Becerikli Y., 2005, NEW FUZZY APPROACH E

[4]

Interval-valued fuzzy sets constructed from matrices: Application to edge detection [J].

Bustince, H. ;

Barrenechea, E. ;

Pagola, M. ;

Fernandez, J. .

FUZZY SETS AND SYSTEMS, 2009, 160 (13) :1819-1840

[5]

Castro JR, 2008, LECT NOTES COMPUT SC, V4750, P104

[6]

ELKHAMY SE, 2000, 17 NRSC 2000 MIN EG

[7]

A morphological gradient approach to color edge detection [J].

Evans, Adrian N. ;

Liu, Xin U. .

IEEE TRANSACTIONS ON IMAGE PROCESSING, 2006, 15 (06) :1454-1463

[8]

A robust visual method for assessing the relative performance of edge-detection algorithms [J].

Heath, MD ;

Sarkar, S ;

Sanocki, T ;

Bowyer, KW .

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1997, 19 (12) :1338-1359

[9]

A high performance edge detector based on fuzzy inference rules [J].

Hu, Liming ;

Cheng, H. D. ;

Zhang, Ming .

INFORMATION SCIENCES, 2007, 177 (21) :4768-4784

[10]

Kuo YH, 1997, PROCEEDINGS OF THE SIXTH IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOLS I - III, P1069, DOI 10.1109/FUZZY.1997.622858

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