Implementation of Growth Management System of Strawberries Using Statistical Regression Model and Image Processing Techniques

• 발행기관: 한국자료분석학회
• 저자명: 조완현(Wanhyun Cho) 김상균(Sangkyoon Kim) 나명환(MyungHwan Na) 김덕현(Deok Hyeon Kim)
• 간행물 정보: 『Journal of The Korean Data Analysis Society (JKDAS)』Vol.22 No.1, 13~22쪽, 전체 10쪽
• 주제분류: 자연과학 > 통계학
• 파일형태: PDF
• 발행일자: 2020.02.28

영문 초록

In this paper, we try to develop a growth management system that can maximize the harvest by examining frequently the growing status of fruit trees using statistical regression model and image processing technique. First, we segment the background, stem and strawberry body from a strawberry image. Second, we calculate the height and width of the strawberry by counting number of pixels from the grid given in the background. Third, a multiple regression model is used to derive a predictive function that can predict its weight from the given height and width of strawberries. Fourth, the accuracy of the prediction is verified by comparing the actual value with the predicted value of the weight of the strawberry using the verification data. Fifth, we conducted experiments using verification images to verify the performance of the constructed prediction model. From the experimental results, the value of the coefficient of determination for the constructed model is 0.98771, which is very high value. Finally, based on the algorithms derived so far, we have developed a platform that can actually be used to manage strawberry growth in farms.

목차

1. Introduction

2. Literature review

3. Growth management system

4. Experimental results

5. Conclusion

References

키워드

growth management system strawberry image statistical regression model image processing techniques weight prediction model