Potato skin defect detection and classification through image processing

Lance Archael G. Espiritu Santo; Russel John D. Placido; Noel B. Linsangan

doi:10.1117/12.2623167

16 February 2022 Potato skin defect detection and classification through image processing

Lance Archael G. Espiritu Santo, Russel John D. Placido, Noel B. Linsangan

Proceedings Volume 12083, Thirteenth International Conference on Graphics and Image Processing (ICGIP 2021); 1208319 (2022) https://doi.org/10.1117/12.2623167
Event: Thirteenth International Conference on Graphics and Image Processing (ICGIP 2021), 2021, Kunming, China

Abstract

Upon progression of how to detect a quality of a potato whether it may be a normal or a diseased potato. Potatoes are a tuber crop that populated 60% of the total crop production. Having potatoes that are green on its skin or even thumbnail marks on it is a sign of it not being healthy to consume. This paper presents a research and development to the quality detection of a potato with image processing and support vector machine. The prototype should be able to detect the skin of a potato if it has thumbnail marks and green skin with the support of Microcomputer Raspberry Pi 4 B and an integrated Raspberry Pi Camera 1.3 for image processing and machine learning. With Python as a language used in the creation of the system a series of function such as OpenCV, SKLearn, Image Acquisition, Image processing, Canny Edge, Gaussian Blur, area, and length plotting, and SVM. Fifteen samples of varying potatoes from green skin, thumbnail crack, and normal to know the effectiveness of the design giving a total of ninety photos per sample that gives a result of 96.67% detection accuracy. Hence the system is an effective method on detecting the said defects on the skin of the potato.

Citation Download Citation

Lance Archael G. Espiritu Santo, Russel John D. Placido, and Noel B. Linsangan "Potato skin defect detection and classification through image processing", Proc. SPIE 12083, Thirteenth International Conference on Graphics and Image Processing (ICGIP 2021), 1208319 (16 February 2022); https://doi.org/10.1117/12.2623167

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
11 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Image processing

Skin

RGB color model

Edge detection

Image classification

Image enhancement

Cameras

Show All Keywords

Keywords/Phrases

Search In:

Publication Years