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A New Approach for Edge Detection: Application to Gray Images

G. Wiselin Jiji*, L. Ganesan**

* Head of the Departmentof Computer Science & Engineering, Dr.SivanthiAditanar College of Engineering, Tiruchendur.

** Head of the Department of Computer Science & Engineering, A. C. College of Engineering & Technology, Karaikudi.

Periodicity:May - July'2008
DOI : https://doi.org/10.26634/jfet.3.4.605

Abstract

Textures are replications, symmetries and combinations of various basic patterns, usually with some random variation one of the gray-level statistics. Detecting of object boundaries is an important step to analyze of an image. The main objective is to locate prominent edges in an image. In the proposed scheme, fuzzy concept is used. Here the texture number is reduced to 2030 in Base5 fuzzy schemes. By combining the traditional edge detection techniques with proposed texture measure can solve this problem. Promising results are obtained when locating texture boundaries of some of the Brain images and texture images and it shows a good method of extracting information that is crucial to a successful intensity based edge detection for detecting texture edges of texture images.

Keywords

Edge, Fuzzy Texture Unit, Fuzzy Texture Spectrum.

How to Cite this Article?

G. Wiselin Jiji and L. Ganesan (2008). A New Approach for Edge Detection: Application to Gray Images. i-manager’s Journal on Future Engineering and Technology, 3(4), 40-45. https://doi.org/10.26634/jfet.3.4.605

References

[1].D.Marr and E.Hildreth ,:Theory of edge detection", proc E.Sonc.London B207 ,187-217,1980.

[2].T.Y.Young and K.S.Fu(eds),"Handbook of pattern Recognition and image processing",Academic press Orlando ,Florida,1986.

[3]. J. F. Haddon, "Generalised threshold selection for edge detection". Pattern Recognition 21,195-203,1988.

[4]. R. M. Haralick, "Statistical and structural approaches to texture", proc.lEEE 67,786-804 1979.

[5]. D. C. He, L. Wang and J. Guibert, "Texture feature extraction". Pattern Recognition Lett,6,269-2 73,1987.

[6]. D. C. He, L. Wang and J. Guibert, "Texture discrimination based on optimal utilization of texture features". Pattern Recognition 21,141-146,1988,

[7]. R. M. Haralick ,K. Shanmugan and I. Dinstein, "Textural features for image classification", IEEE Trans.Syst.Man. cyber.SMC -3(6),610-621,1973.

[8]. R. L. Kashyap and K. B. Eom, "Texture boundary detection based on the long correlation model",/FEE Trans. Pattern Analysis mach. Intell. 11(1 ),58- 67.1989.

[9]. D. C. He, L. Wang, "Texture Unit, texture spectrum and Texture analysis", IEEE Trans.Geosci.Remote Sensing 56(1 ),61-66,1990.

[10]. D. C. He, L. Wang, "A new statistical approach for texture analysis", Photogrammetric Engg. Remote Sens/ng56(l), 61-66,1990.

[11]. D. C. He, L. Wang, "Texture Classification using texture Spectrum", Pattern recognition 23, 905-910, 1990.

[12]. He D. C and Li. Wang, "Texture Unit, Texture Spectrum and Texture Analysis", IEEE Trans.Geo Science RemoteSensing. 28(4), 509-512,1990.

[13]. D. C. He, L. Wang, "Texture features based on texture spectrum" Pattern recognition 24,391 -399,1991,

[14]. Bovik, A. C., Clark, M. and Geisler, W. S. "Multichannel Texture Analysis Using Localized Spatial Filters", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 12, No. 1, pp. 55-73,1990

[15]. Dunn, D. and Higgins, W. E. "Optimal Gabor Filters for Texture Segmentation", IEEE Transactions on Image Processing, Vol.4, No. 7, pp. 947- 964,1995

[16]. Lu, S., Hernandez, J. E., Clark, G. A. "Texture Segmentation by Clustering of Gabor Feature Vectors", IEEE Proc. ofthelnt. Conf, on Artificial Neural Networks I, 683-687,1991

[17]. Jain, A. K. and Farrokhnia, F. "Unsupervised Texture Segmentation Using Gabor Filters", Pattern Recognition, Vol. 24, No. 12, pp. 1167-1186,1999

[18]. T. Ojala, M. pietikainen and D. Harwood. "Performance evolution of texture measures with class based on kullback discrimination of distributions". In IAPR international conference on Pattern Recognition, Vol.A, pp 582-585., Jerusalem, Israel, Sep. 1994.

[19], T. Ojala, M. pietikainen and D. Harwood, "A Comparative study of texture measures with Classification based on feature distributions". Pattern Recognition, 29: 51 -59,1996.

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