Yield Estimation of Pomegranate Using Image Processing Techniques
Santi Kumari Behera1, Abhishek Pattnaik2, Amiya Kumar Rath3, Nalini Kanta Barpanda4, Prabira Kumar Sethy5
1Santi Kumari Behera, Assistant Professor, Department of Computer Science and Engineering, Veer Surendra Sai University of Technology, Burla.
2Abhishek Pattanaik, M.Tech, Department of Communication System Engineering, Sambalpur University Institute of Information Technology, Sambalpur University, Burla, Odisha.
3Amiya Kumar Rath, Professor, Department of Computer Science and Engineering, Veer Surendra Sai University of Technology, Burla.
4Dr. Nalini Kanta Barpanda, Department of Electronics, Sambalpur University, Burla, Odisha.
5Prabira Kumar Sethy, Assistant Professor, Department of Electronics, Sambalpur University, Burla, Odisha.
Manuscript received on 10 April 2019 | Revised Manuscript received on 17 April 2019 | Manuscript Published on 26 April 2019 | PP: 798-803 | Volume-8 Issue-6S April 2019 | Retrieval Number: F60990486S19/19©BEIESP
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© 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: Yield estimation of pomegranate is an important aspect for planning many tasks such as storing, packaging and exporting. To measure the quantity of fruits on-tree manually is quite difficult and time consuming. The image processing based automated system is an influential technical competence to measure the quantity of pomegranate fruits. This paper consists two approach to detect and count pomegranate fruit using on-tree images i.e. first approach is based on color thresholding with circular Hough transform (CHT) & second approach based on K-means clustering with Circular Hough transform (CHT) and the performance of both method is evaluated by correlation co-efficient R2 i.e. 0.6888 & 0.7652 respectively.
Keywords: Circle Hough Transform, Color Thresholding, Fruit Counting, fruit Detection, K-Means Clustering, Pomegranate.
Scope of the Article: Communication