会议专题

Detect black germ in wheat using machine vision

The objective of this research is to develop algorithm to recognize black germ wheat based on image processing. The sample used for this study involved wheat from major producing areas of China. Images of wheat were acquired with a color linear CCD machine vision system. Each image was pre-processed to correct color offset. Then double-threshold method was used to segment black germ from background and other area in wheat Combining morphological and extracted feature gave a highly acceptable classification. The high classification accuracies obtained using a small number of features indicate the potential of the algorithm for on-line inspection of black germ wheat in industrial environment The overall average classification accuracy among the involved varieties reaches above 93%. This paper presents the significant elements of the computer vision system and emphasizes the important aspects of the image processing technique.

black germ wheat image processing

FN Chen F. Cheng YB Ying

College of Biosystems Engineering and Food Science Zhejiang University, Hangzhou, China

国际会议

2011 Fourth International Conference on Intelligent Computation Technology and Automation(2011年第四届智能计算技术与自动化国际会议 ICICTA 2011)

深圳

英文

54-57

2011-03-28(万方平台首次上网日期,不代表论文的发表时间)