Article: Enhancement-based background separation techniques for fruit grading and sorting Journal: International Journal of Intelligent Systems Technologies and Applications (IJISTA) 2019 Vol.18 No.3 pp.223 - 256 Abstract: Image processing plays a remarkable role in the automation of fruit grading and sorting. While grading the fruit, accurate extraction of fruit object from the image (background separation) is the chief concern. For extraction of fruit, appropriate segmentation technique is employed; and to accomplish it accurately, enhancement must be performed prior to segmentation. However, majority of the researchers emphasised over fruit segmentation alone. This communication is intended to show the potential of enhancement techniques when combined with fruit image segmentation. Besides, it presents a comparative analysis of enhancement-based background separation techniques for fruit grading and sorting. For this purpose, four main techniques, namely, contrast limited adaptive histogram equalisation (CLAHE) method, Gaussian filter, median filter and Wiener filter were utilised for enhancement and basic global thresholding, adaptive thresholding, Otsu thresholding and Otsu-HSV thresholding were applied for segmentation. 16 sub-models were developed by combining each enhancement method with every segmentation technique. Afterwards, the image quality of the sub-models was validated using quantitative as well as qualitative analyses. Test results demonstrate that CLAHE/Otsu-HSV model outperformed the others for fruit grading and sorting. Inderscience Publishers - linking academia, business and industry through research

Title: Enhancement-based background separation techniques for fruit grading and sorting

Authors: Jasmeen Gill; Akshay Girdhar; Tejwant Singh

Addresses: IKG Punjab Technical University, Kapurthala, Punjab, India ' IT Department, GNE, IKG Punjab Technical University, Kapurthala, Punjab, India ' Applied Sciences Department, SBBSIET, IKG Punjab Technical University, Kapurthala, Punjab, India

Abstract: Image processing plays a remarkable role in the automation of fruit grading and sorting. While grading the fruit, accurate extraction of fruit object from the image (background separation) is the chief concern. For extraction of fruit, appropriate segmentation technique is employed; and to accomplish it accurately, enhancement must be performed prior to segmentation. However, majority of the researchers emphasised over fruit segmentation alone. This communication is intended to show the potential of enhancement techniques when combined with fruit image segmentation. Besides, it presents a comparative analysis of enhancement-based background separation techniques for fruit grading and sorting. For this purpose, four main techniques, namely, contrast limited adaptive histogram equalisation (CLAHE) method, Gaussian filter, median filter and Wiener filter were utilised for enhancement and basic global thresholding, adaptive thresholding, Otsu thresholding and Otsu-HSV thresholding were applied for segmentation. 16 sub-models were developed by combining each enhancement method with every segmentation technique. Afterwards, the image quality of the sub-models was validated using quantitative as well as qualitative analyses. Test results demonstrate that CLAHE/Otsu-HSV model outperformed the others for fruit grading and sorting.

Keywords: digital image processing; segmentation; enhancement; fruit grading and sorting; background separation; Otsu-HSV segmentation.

DOI: 10.1504/IJISTA.2019.099342

International Journal of Intelligent Systems Technologies and Applications, 2019 Vol.18 No.3, pp.223 - 256

Received: 14 May 2017
Accepted: 06 Sep 2017
Published online: 29 Apr 2019 *

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Title: Enhancement-based background separation techniques for fruit grading and sorting

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