Abstract
Aiming at the shortcomings of traditional apple defect detection methods such as high labor intensity, low productivity and high false positive rate,the apple defect detection algorithm is proposed based on visible light-infrared light image fusion. The algorithm uses different fusion methods for high and low frequency wavelet coefficients of visible and infrared images to obtain more prominent feature images. The results of simulations show that the recognition rate can reach 96% in the detection of apple fruit with scratches, bumps, fruit stems/flower buds and intact fruits, in addition, the recognition accuracy rate for scratches can reach 92%, and in the detection of fruit stems, flower buds and intact fruit, the accuracy rate can reach 100%. It fully meets the needs of apple's online detection and classification.
Publication Date
9-28-2018
First Page
135
Last Page
138
DOI
10.13652/j.issn.1003-5788.2018.09.028
Recommended Citation
Qianhui, CHEN and Degang, WU
(2018)
"Algorithm on apple defect detection based on visible light-infrared light image fusion,"
Food and Machinery: Vol. 34:
Iss.
9, Article 28.
DOI: 10.13652/j.issn.1003-5788.2018.09.028
Available at:
https://www.ifoodmm.cn/journal/vol34/iss9/28
References
[1] 周渝人, 耿爱辉, 张强, 等. 基于压缩感知的红外与可见光图像融合[J]. 光学精密工程, 2015, 23(3): 855-863.
[2] 黄慧, 张宝辉, 席峰, 等. 基于目标增强的红外与可见光图像融合技术研究[J]. 红外技术, 2017, 39(10): 908-913.
[3] 田裕鹏. 红外辐射成像无损检测关键技术研究[D]. 南京: 南京航空航天大学, 2009: 23-50.
[4] 郭道峰, 王家森, 刘忠齐. 球面热源辐射特性的研究[J]. 中国医学影像技术, 2002, 18(8): 830-833.
[5] BARANOWSKI P, MAZUREK W, WALCZAK B W, et al. Detection of early apple bruises using pulsed-phase thermograp-hy[J]. Postharvest Biology and Technology, 2009,53(1): 91-100.
[6] VARITH J, HYDE G M, BARITELLE A L. et al. Non-contact bruise detection in apples by thermal imaging[J]. Innovative Food Science and Emerging Technologies, 2003, 4(1): 211-218.