Enhanced Object Detection using Generalized Hough Transform and RANSAC
Rammah Yousef1, Pranaw Kumar2, Nabhan Yousef3

1Pranaw Kumar*, Assistant Professor in School of Electronics Engineering, Kalinga Institute of Industrial Technology University, Bhubaneswar, Odisha, India.
2Rammah Yousef, Studying M.Tech in Communication Engineering in KIIT University, Bhubaneswar, India.
3Nabhan Yousef, Studying M.Tech in Information Communication Technology in Marwadi University, Rajkot, Gujarat, India.

Manuscript received on September 16, 2019. | Revised Manuscript received on 24 September, 2019. | Manuscript published on October 10, 2019. | PP: 2046-2052 | Volume-8 Issue-12, October 2019. | Retrieval Number: L32541081219/2019©BEIESP | DOI: 10.35940/ijitee.L3254.1081219
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© The Authors. 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: In this paper object detection process has been implemented using the combination of some robust algorithms. The algorithms used are SIFT, GHT and RANSAC. Two models have been proposed which using two of the above mentioned algorithms. In model one features extraction by SIFT has been processed using Generalized Hough Transform (GHT) , where in other model improved RANSAC has been used to eliminate the mismatches in order to achieve better recognition resolution. Overall GHT is found to be superior technique to achieve object detection efficiently.
Keywords: Object Detection, SIFT, General hough Transform, RANSAC.
Scope of the Article: Algorithm Engineering