DEVELOPMENT OF MULTISPECTRAL ALGORITHM FOR DETECTION OF CRACKED TOMATOES

作者：Yang C C; Kim M S^*; Cho B K; Lee H; Chao K; Lee H; Jeong D; Lefcourt A M; Chan D E

来源：Transactions of the ASABE, 2013, 56(4): 1581-1588.

• Crack detection
• Food safety
• Hyperspectral images
• Line-scan
• Multispectral algorithm
• Tomato

Tomato cracks present a potential food safety risk by allowing internalization of pathogens. This article reports a first-step study for the development and evaluation of a simple multispectral algorithm for the detection of defect cracked tomatoes. Analysis of hyperspectral visible/near-infrared tomato images identified two wavebands, 749 nm and 887 nm, for computation of two decision functions to detect defect cracked tomatoes and to differentiate them from normal tomatoes. Detection of defect cracked tomatoes was based on spectral identification of non-skin pixels coupled with quantitative evaluation of the number of non-skin pixels compared to the total image pixels for each tomato. The algorithm successfully classified 94% of the normal tomatoes and 99% of the defect tomatoes used in this study. The results suggest that this multispectral spectral imaging-based method has potential for implementation in line-scan imaging systems as a tool for rapid food inspection on high-speed tomato processing lines.

• 出版日期2013-8