A Survey on Fuzzy Logic Based Approaches for Edge Detection
Abstract
A digital picture is a distribution of gray values over a predefined grid of specified image size. Digital image processing may also be said as a subset as a branch of science, where any given image can be transformed to arrays of small integers called pixels or snapshots representing a physical number such as scene radians and the digital photograph processing ways stems from two most important utility areas: growth of pictorial expertise for human figuring out and processing of photograph information for storage, transmission and representation for independent computing device belief .Edges symbolize boundaries and side detection can be stated as some of the complicated assignment in photo processing. Aspect detection is a procedure which significantly reduces the amount of knowledge and filters out vain understanding while retaining the foremost structural homes in an photograph. Area detection has many functions in snapshot processing and laptop imaginative and prescient and will probably be an foremost method in each biological and robotic vision.
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Abraham, V. K. 2002. The International Conference
on Commercial Floriculture, Summary Report, 11-12 August, Bangalore. 2. HENG-DA, Cheng and YING, Sun. A Hierarchical Approach to Color Image Segmentation Using Homogeneity. 2000, IEEE Transactions on Image Processing 9, pp. 2071-2082.
CANNY, John. A computational Approach to Edge Detection. 1986. IEEE Transactions on Pattern Analysis and Machine Intelligence 8. Vol. 6, pp. 679-698.
LIANG, Lily, Rui and LOONEY, Carl, G. Competitive fuzzy edge detection. 2003, Applied Soft Computing 3, pp. 123-137.
DERICHE, Rachid and MONGA, Olivier. 3D Edge Detection Using Recursive Filtering: Application to Scanner Images. Institut National de Recherche en Informatique et en Automatique (INRIA). Domaine de Voluceau :s.n., 1988.
SOLAIMAN, Basel, R.Fiset and F.Cavayas. Automatic road extraction using fuzzy mask concepts. Amburg,Germany : s.n., 1999. IGARSS’99. pp. 894-896.
Chamorro-Martinez, J., Sanchez, D. and Prados-Suarez, B. Segmenting Colour Images on the Basis of a Fuzzy Hierarchical Approach. Granada :s.n., 2003, Mathware& Soft Computing 10, pp. 101-115.
LIMING, Hu, HENG-DA, Cheng and MING, Zhang. A high performance edge detector based on fuzzy inference rules. 2007, Information Sciences 177, pp. 4768-4784.
J.C. Bezdek, R. Chandrasekhar and Y. Attikiouzel, “A geometric approach to edge detection”,IEEE Transactions on Fuzzy Systems, vol. 6, no. 1, pp. 5275, 1998.
K.H.L. Ho, “FEDGE - fuzzy edge detection by fuzzy categorization and classification of edges”,IJCAI’95 Workshop, pp. 182-196.
S.K. Pal and D.K. Dutta Majumder, Fuzzy Mathematical approach to pattern recognition, 1985, John Wiley and Sons.
Russo, “FIRE operators for image processing”, Fuzzy Sets and Systems, vol. 103, no. 2, pp. 265-275, 1999 [CrossRef].
H.R. Tizhoosh, Fuzzy Image Processing, 1997, Springer, Heidelberg.
H.R. Tizhoosh, H. Hauecker, B Jhne, H Hau¿¿ecker and P Gei¿¿ler, “Fuzzy Image Processing: An Overview” in Handbook on Computer Vision and Applications, vol. 2, pp. 683-727, 1999, Academic Press.
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