IJSER Home >> Journal >> IJSER
International Journal of Scientific and Engineering Research
ISSN Online 2229-5518
ISSN Print: 2229-5518 7    
Website: http://www.ijser.org
scirp IJSER >> Volume 3,Issue 7,July 2012
3D Image Processing Operations
Full Text(PDF, )  PP.244-250  
Mrs. A. Padmapriya, S.Vigneshnarthi
Image processing and pattern recognition has become a powerful technique in many areas. This includes Engineering, Computer Science, Statistics, Information Science, Physics, Chemistry and Medicine. Anyone who wants to extract data from image or visual project, image processing is required. Most of the image processing software's are able to process two dimensional images alone. This paper implements three basic image processing operations namely enhancement, blur and segmentation. Each of the operation can be implemented using a variety of algorithms.The algorithms are implemented using and their performance are compared in this paper.The proposed work produces better result of 3D images also.
[1] ABDUL HALIM BIN BABA. image processing learning tool-edge detection bachelor degree. university of technology malaysia 1996.

[2] FIONN MURTAGH. Image Processing data analysis. the multi-scale approach. University of Ulster.

[3] Fundamentals of image processing, hany.farid@dartmouth.edu .(http://www.cs.dartmouth.edu/~farid)

[4] JEAN-LUC STARCK, centre d’ etudes de Saclay, Fionn Murtagh. Image processing and data analysis the multiscale approach. University of Ulster.

[5] LOUIS J.GALBIATI, JR. machine vision and digital image processing fundamentals. Prentice-Hall International Editions.

[6] S. K. MITRA AND H. LI, “a new class of nonlinear filters for image enhancement, ”in Proc. IEEE int. Conf. Acoustics, Speech, Signal Processing, Toronto, Ont., Canada, may 14–17, 1991, pp. 2525–2528.

[7] G. RAMPONI, N. STROBEL, S. K. MITRA, AND T. YU, “nonlinear unsharp masking methods for image contrast enhancement,” J. Electron. Image, vol. 5, pp. 353–366, July 1996.

[8] G. RAMPONI, “A cubic unsharp masking technique for contrast enhancement,” Signal Process., vol. 67, pp. 211–222,June 1998.

[9] Y. H. LEE AND S. Y. PARK, “A study of convex/concave edges and edge enhancing operators based on the laplacian,” IEEE Trans. Circuits Syst., vol. 37, pp. 940–946, July 1990.

Untitled Page