Fuzzy Mathematical Morphology approach in Image Processing
Morphological operators transform the original image
into another image through the interaction with the other image of
certain shape and size which is known as the structure element.
Mathematical morphology provides a systematic approach to analyze
the geometric characteristics of signals or images, and has been
applied widely too many applications such as edge detection,
objection segmentation, noise suppression and so on. Fuzzy
Mathematical Morphology aims to extend the binary morphological
operators to grey-level images. In order to define the basic
morphological operations such as fuzzy erosion, dilation, opening
and closing, a general method based upon fuzzy implication and
inclusion grade operators is introduced. The fuzzy morphological
operations extend the ordinary morphological operations by using
fuzzy sets where for fuzzy sets, the union operation is replaced by a
maximum operation, and the intersection operation is replaced by a
minimum operation.
In this work, it consists of two articles. In the first one, fuzzy set
theory, fuzzy Mathematical morphology which is based on fuzzy
logic and fuzzy set theory; fuzzy Mathematical operations and their
properties will be studied in details. As a second part, the application
of fuzziness in Mathematical morphology in practical work such as
image processing will be discussed with the illustration problems.
[1] P.Burillo, N.Frago, R.Fuentes, Fuzzy Morphological
Operators in Image Processing, Marthware & Soft
Computing 10 (2003), 8-100
[2] P.Burillo, N.Frago, R.Fuentes, Generation Fuzzy
Morphological Morphologies, Marthware & Soft
Computing 8 (2003), 31-46
[3] Alper PAHSA, Morphological Image Processing with
Fuzzy Logic, Havacilik Ve Uzay Teknolojileri Dergisi,
Ocak, Cilt 2 Sayi 3 (2006), 27-34
[4] Bouchet, A.,Pastore, J., Ballarine, V, Segmentation of
Medical Image using Fuzzy Mathematical Morphology,
Jcs & T Vol .7 No.3, (2007)
[5] Andrzej Piegat, A New Defination of the Fuzzy Set, Int.J.
Appl. Math. Comput. Sci. Vol.1, Ir No.1 (2005), 12-140
[6] Antony T. Popov, General Approach for Fuzzy
Mathematical Morphology, Proceeding of the 8th
International Symposium on Mathematical Morphology,
V.1 (2007), 39-48
[7] Richard Alan Peters II, Mathematical Morphology for
Angle-valued Images, proceeding of the SPIE, Nonlinear
Image Processing VIII, Volume 3026 (1997), 84-94
[8] Wayne, Lin Wei-Cheng, Mathematical Morphology and
Its Applications on Image Segmentation, Dept. of
Computer Science and Information Engineering,
National Taiwan University, Jund 7 (2000)
[9] Preechaya Srisombut, Morphological Image Processing
Gradute School of Information Sciences and
Engineering, Tokyo Institute of Technology for IP
Seminar, 4 November (2004)
[10] Nata. a Sladoje, Fuzzy Sets and Fuzzy Techniques,
Lecture 11, Defuzzication, Centre for Image Analysis,
Uppsala University, Februrary 28, (2007)
[1] P.Burillo, N.Frago, R.Fuentes, Fuzzy Morphological
Operators in Image Processing, Marthware & Soft
Computing 10 (2003), 8-100
[2] P.Burillo, N.Frago, R.Fuentes, Generation Fuzzy
Morphological Morphologies, Marthware & Soft
Computing 8 (2003), 31-46
[3] Alper PAHSA, Morphological Image Processing with
Fuzzy Logic, Havacilik Ve Uzay Teknolojileri Dergisi,
Ocak, Cilt 2 Sayi 3 (2006), 27-34
[4] Bouchet, A.,Pastore, J., Ballarine, V, Segmentation of
Medical Image using Fuzzy Mathematical Morphology,
Jcs & T Vol .7 No.3, (2007)
[5] Andrzej Piegat, A New Defination of the Fuzzy Set, Int.J.
Appl. Math. Comput. Sci. Vol.1, Ir No.1 (2005), 12-140
[6] Antony T. Popov, General Approach for Fuzzy
Mathematical Morphology, Proceeding of the 8th
International Symposium on Mathematical Morphology,
V.1 (2007), 39-48
[7] Richard Alan Peters II, Mathematical Morphology for
Angle-valued Images, proceeding of the SPIE, Nonlinear
Image Processing VIII, Volume 3026 (1997), 84-94
[8] Wayne, Lin Wei-Cheng, Mathematical Morphology and
Its Applications on Image Segmentation, Dept. of
Computer Science and Information Engineering,
National Taiwan University, Jund 7 (2000)
[9] Preechaya Srisombut, Morphological Image Processing
Gradute School of Information Sciences and
Engineering, Tokyo Institute of Technology for IP
Seminar, 4 November (2004)
[10] Nata. a Sladoje, Fuzzy Sets and Fuzzy Techniques,
Lecture 11, Defuzzication, Centre for Image Analysis,
Uppsala University, Februrary 28, (2007)
@article{"International Journal of Information, Control and Computer Sciences:50652", author = "Yee Yee Htun and Dr. Khaing Khaing Aye", title = "Fuzzy Mathematical Morphology approach in Image Processing", abstract = "Morphological operators transform the original image
into another image through the interaction with the other image of
certain shape and size which is known as the structure element.
Mathematical morphology provides a systematic approach to analyze
the geometric characteristics of signals or images, and has been
applied widely too many applications such as edge detection,
objection segmentation, noise suppression and so on. Fuzzy
Mathematical Morphology aims to extend the binary morphological
operators to grey-level images. In order to define the basic
morphological operations such as fuzzy erosion, dilation, opening
and closing, a general method based upon fuzzy implication and
inclusion grade operators is introduced. The fuzzy morphological
operations extend the ordinary morphological operations by using
fuzzy sets where for fuzzy sets, the union operation is replaced by a
maximum operation, and the intersection operation is replaced by a
minimum operation.
In this work, it consists of two articles. In the first one, fuzzy set
theory, fuzzy Mathematical morphology which is based on fuzzy
logic and fuzzy set theory; fuzzy Mathematical operations and their
properties will be studied in details. As a second part, the application
of fuzziness in Mathematical morphology in practical work such as
image processing will be discussed with the illustration problems.", keywords = "Binary Morphological, Fuzzy sets, Grayscalemorphology, Image processing, Mathematical morphology.", volume = "2", number = "6", pages = "1829-7", }