Fruits Ripening Analysis System using Image Processing Technology

Main Article Content

Aekkarat Suksukont
Chonlathis Santingamwong
Watcharaphon Khamkhaek
Sasicha Pansuwan

Abstract

This research presents the fruits ripening analysis system using image processing technology is objective to check the ripeness of the fruit in real time and facilitate farmers. To reduce fruit spoilage problems that may occur. In this research using NI Vision Builder was conjunction with a webcam and image processing technology to assist in analysis. The experiment was found that fruits ripening analysis system using image processing technology able to count the number of fruits accuracy 100% and be able to analyze the ripeness of the fruits accuracy 95%. Allowing farmers and users answer the satisfaction questionnaire about system performance results were in the criteria of very satisfied with the most satisfied, respectively.

Downloads

Download data is not yet available.

Article Details

How to Cite
[1]
A. Suksukont, C. Santingamwong, W. Khamkhaek, and S. Pansuwan, “Fruits Ripening Analysis System using Image Processing Technology”, JIST, vol. 12, no. 1, pp. 61–66, Jun. 2022.
Section
Research Article: Programming (Detail in Scope of Journal)

References

Tanut Bh. and Kamsuwan N., “A Prototype Development of Marigold Classification by Image Processing,” Journal of Science and Technology Nakhon Sawan Rajabhat University, vol. 11, no. 13, pp. 79-92, 2019.

Kajornlap W. and Janpho J., “Lemon Size Sorting Machine,” Thesis in Production Techniques, 2015.

Suksukont A., Chunlahanak J., Buain Ch. and Suwannasin K., “Soft / Mature Lemons Counting and Analysis System with Image Processing Techniques,” The 11th Benjamitra Network National and International Conference, May 27, pp. 86-93. 2021.

Priwthaisong K., “Automatic Color Sorting Machine on Conveyor Systems Controlled by Arduino,” Association of Private Higher Education Institutions of Thailand, vol. 5 no. 1, pp. 15-21, 2016.

Jing L., Junzheng W. and Jiali M., “Color moving object Detection Method Based on Automatic Color Clustering,” Proceedings of the 33rd Chinese Control Conference, July 28-30, pp. 7232-7235, 2014.

Gokul P.R., Raj S. and Suriyamoorthi P., “Estimation of Volume and Maturity of Sweet Lime Fruit using Image Processing Algorithm,” International Conference on Communications and Signal Processing (ICCSP). April 2- 4, pp. 1227-1229, 2015.

Pandey C., Sethy P.K., Biswas P., Behera S.K. and Khan M.R., “Quality Evaluation of Pomegranate Fruit using Image Processing Techniques”, International Conference on Communication and Signal Processing (ICCSP). July 28-30, pp. 38-40, 2020.

Sotirov S.I., Zhelyazkov S.P., Marudova M.G., Zsivanovits G., and Tokamkov D.M., “Embedded System for Fruit Image Processing,” International Scientific Conference Electronics, September 16-18, pp. 1-3, , 2020.