The week's pick
Reseach Article
An Advance Approach to Select Initial Seed Pixel using Edge Detection
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 75 - Number 8 |
| Year of Publication: 2013 |
| Authors: Rajesh Gothwal, Deepak Gupta, Shikha Gupta |
10.5120/13132-0500
|
Rajesh Gothwal, Deepak Gupta, Shikha Gupta . An Advance Approach to Select Initial Seed Pixel using Edge Detection. International Journal of Computer Applications. 75, 8 ( August 2013), 27-31. DOI=10.5120/13132-0500
Abstract
This paper proposes a method of initial seed pixel selection used for image segmentation based on edge detection technique. Initial pixel seed selection is the crucial and starting stage of image segmentation. This method is based on RGB color model. In this paper author use the gradient magnitude of the Red, Green and Blue components of true color image. Two type of information are used: non-edge information and similarity behavior of pixels to its neighbors. Edge detection technique is used to select initial seed pixel selection by computing gradient of the image intensity function. The Gradient magnitude provides image with regions having high intensity variation. The threshold value is used to obtain seed pixels and its value depends on the nature of the image. In this paper the comparative analysis of various images with different Edge Detection techniques is presented. The analysis of images with different edge detection techniques is presented using image processing tool MATLAB 7. 5. 0. It has been shown that gradient based edge detection techniques provides similar and better result than other edge detection techniques.
References
- Adams, R. , Bischof, L. , "Seeded region 1growing", IEEE Transactions on Pattern anlysis and Machine Intelligence, vol. 16, page 641-647, 1994.
- Om Prakash Verma, Madasu Hanmandlu, Seba Susan, Muralidhar Kulkarni and Puneet Kumar Jain "A Simple Single Seeded Region Growing Algorithm for Color Image Segmentation using Adaptive Thresholding" IEEE 978-0-7695-4437, 2011.
- Frank Y. Shih and Shouxian Cheng "Automatic seeded region growing for color image segmentation" Image and vision computing 23, 877-886, 2005.
- N. Chowdhury, B. Banerjee , T. Bhattacharjee "color image segmentation technique using "natural grouping" of pixels" 1985-2304, 2010.
- Gracia Guzzarria "Automatic Image Segmentation by Dynamic Region Growth and Multiresolution Merging ", 18-10, 2275 – 2288, 2009.
- A. V. Anjikar and V. K. Shandilya "Effective method of Initial Seed Selection Used for Color Image Segmentation" IJCTA, Vol 2 (3), 431-432.
- Thodeti Srikanth, Prof P. Pradeep Kumar, Ashwin Kumar "color image segmentation using watershed algorithm" IJCSIT, vol. 2 (5), 2332-2334,2011.
- Changmin Zhang, Shuaiqi Zhang, Junxia Wu, Shaoxiong Han "an improved watershed algorithm for color image segmentation" IEEE 978-0-7695-4647-6/12 2012.
- R. C. Gonzalez and R. E. Woods, digital image processing, Pearson education, 2002.
- Malik sikandar hayat khiyal, aihab khan, and amna bibi, "modified watershed algorithm for segmentation of 2D images" IISIT volume 6, 2009.
- Raman Maini, Dr. Himanshu Aggarwal, "Study and Comparison of Various Image Edge Detection Techniques" IJIP Volume (3): Issue (1).
- Mamta Juneja, Parvinder Singh Sandhu, "Performance Evaluation of Edge Detection Techniques for Images in Spatial Domain", 1793-8201, International Journal of Computer Theory and Engineering, Vol. 1, No. 5, December, 2009.
- Vineet Saini, Rajnish Garg, "A Comparative Analysis on Edge Detection Techniques Used in Image Processing", IOSRJECE, 2278-2834 Volume 1, Issue 2, PP 56-59, 2012.
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