Abstract
This paper presents a novel method to recognize stem - calyx of an apple using shape descriptors. The main drawback of existing apple grading techniques is that stem - calyx part of an apple is treated as defects, this leads to poor grading of apples. In order to overcome this drawback, we proposed an approach to recognize stem-calyx and differentiated from true defects based on shape features. Our method comprises of steps such as segmentation of apple using grow-cut method, candidate objects such as stem-calyx and small defects are detected using multi-threshold segmentation. The shape features are extracted from detected objects using Multifractal, Fourier and Radon descriptor and finally stem-calyx regions are recognized and differentiated from true defects using SVM classifier. The proposed algorithm is evaluated using experiments conducted on apple image dataset and results exhibit considerable improvement in recognition of stem-calyx region compared to other techniques.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Signal & Image Processing : An International Journal
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
