IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Computer Vision Based Technique for Surface Defect Detection of Apples

Computer Vision Based Technique for Surface Defect Detection of Apples
View Sample PDF
Author(s): C. J. Prabhakar (Kuvempu University, India)and S. H. Mohana (Kuvempu University, India)
Copyright: 2014
Pages: 11
Source title: Research Developments in Computer Vision and Image Processing: Methodologies and Applications
Source Author(s)/Editor(s): Rajeev Srivastava (Indian Institute of Technology (BHU), India), S. K. Singh (Indian Institute of Technology (BHU), India)and K. K. Shukla (Indian Institute of Technology (BHU), India)
DOI: 10.4018/978-1-4666-4558-5.ch007

Purchase

View Computer Vision Based Technique for Surface Defect Detection of Apples on the publisher's website for pricing and purchasing information.

Abstract

The automatic inspection of quality in fruits is becoming of paramount importance in order to decrease production costs and increase quality standards. Computer vision techniques are used in fruit industry for fruit grading, sorting, and defect detection. In this chapter, we review recent approaches for automatic inspection of quality in fruits using computer vision techniques. Particularly, we focus on the review of advances in computer vision techniques for automatic inspection of quality of apples based on surface defects. Finally, we present our approach to estimate the defects on the surface of an apple using grow-cut and multi-threshold based segmentation technique. The experimental results show that our method effectively estimates the defects on the surface of apples significantly more effectively than color based segmentation technique.

Related Content

Aswathy Ravikumar, Harini Sriraman. © 2023. 18 pages.
Ezhilarasie R., Aishwarya N., Subramani V., Umamakeswari A.. © 2023. 10 pages.
Sangeetha J.. © 2023. 13 pages.
Manivannan Doraipandian, Sriram J., Yathishan D., Palanivel S.. © 2023. 14 pages.
T. Kavitha, Malini S., Senbagavalli G.. © 2023. 36 pages.
Uma K. V., Aakash V., Deisy C.. © 2023. 23 pages.
Alageswaran Ramaiah, Arun K. S., Yathishan D., Sriram J., Palanivel S.. © 2023. 17 pages.
Body Bottom