A Simulation Model for Corner Detection in Fruits Foveated Images
K. L. Neela1, P. Mercy Nesa Rani2, T. Rajesh3
1K. L. Neela, Department of Computer Science, University College of Engineering, Thirukkuvalai, Tamil Nadu, India.
2P. Mercy Nesa Rani, School of Social Sciences, College of Post Graduate Studies(Central Agricultural University), Meghalaya
3T. Rajesh, School of Crop Protection, College of Post Graduate Studies(Central Agricultural University), Meghalaya.
Manuscript received on April 05, 2013. | Revised Manuscript received on April 29, 2013. | Manuscript published on May 05, 2013. | PP: 88-91 | Volume-3, Issue-2, May 2013. | Retrieval Number: B1439053213/2013©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Corner detection is a challenging and important research area in computer vision and object recognition systems. However, they have some problems such as sensitive to noise, poor localization. The corner detector -Feature Accelerated Segment Test (FAST) which will be a good locator of corners in foveated images similar to Human Visual Fixations. The feature detector considers pixels in a circular region. This technique creates uniformity over the image area considering the brightness and darkness for estimation that constitutes as corner. The resulting detector will detect very stable features in foveated images. This paper deals with foveation filtering and corner detection to establish foveal location in natural images. The proposed approach is implemented with the help of VC++ language and will provide fine location for all real world applications.
Keywords: Foveation Filtering, Corner Detection, Foveated images, FAST algorithm, Fruit Images.