Adaptive thresholding based segmentation of infected portion of pome fruit. Issue 4 (4th July 2017)

• Record Type: Journal Article
• Authors: Yogesh, ; Dubey, Ashwani Kumar; Agarwal, Abhay; Sarkar, Adrija; Arora, Rajeev
• Is Part Of: Journal of statistics & management systems. Volume 20:Issue 4(2017)
• Page Start: 575
• Page End: 584
• Publication Date: 2017-07-04
• Subjects: Adaptive thresholding -- fruit quality -- pome fruits -- segmentation -- Thresholding; 68T05; Statistics -- Periodicals; Mathematical models -- Periodicals; Mathematical models; Statistics; Periodicals; 519.5
• DOI: 10.1080/09720510.2017.1395177
• Languages: English
• ISSNs: 0972-0510

Abstract

Abstract: In this paper, we elaborate the segmentation of the infected portion of pome fruits. An adaptive thresholding method is applied on pears. Other segmentation methods such as OTSU, region growing, merge and split, greedy snake etc are available. But the main issue is the fixed threshold value for thresholding causes some of the information loss due to improper segmentation. A multi-level thresholding algorithm is developed in this paper. An improved thresholding algorithm not only reduces the processing time but, also improves the segmentation technique. The region of interest after segmentation is then further analyzed to identify the defected portion of pome fruit.