Development of real-time line-scan hyperspectral imaging system for online agricultural and food product inspection

Seung Chul Yoon; Bosoon Park; Kurt C. Lawrence; William R. Windham; Gerald W. Heitschmidt

doi:10.1117/12.850460

20 April 2010 Development of real-time line-scan hyperspectral imaging system for online agricultural and food product inspection

Seung Chul Yoon, Bosoon Park, Kurt C. Lawrence, William R. Windham, Gerald W. Heitschmidt

Author Affiliations +

Proceedings Volume 7676, Sensing for Agriculture and Food Quality and Safety II; 76760J (2010) https://doi.org/10.1117/12.850460
Event: SPIE Defense, Security, and Sensing, 2010, Orlando, Florida, United States

Abstract

This paper reports a recent development of a line-scan hyperspectral imaging system for real-time multispectral imaging applications in agricultural and food industries. The hyperspectral imaging system consisted of a spectrograph, an EMCCD camera, and application software. The real-time multispectral imaging with the developed system was possible due to (1) data binning, especially a unique feature of the EMCCD sensor allowing the access to non-contiguous multispectral bands, (2) an image processing algorithm designed for real-time multispectral imaging, and (3) the design and implementation of the real-time application software. The imaging system was developed as a poultry inspection instrument determining the presence of surface feces on poultry carcasses moving at commercial poultry processing line speeds up to 180 birds per minute. The imaging system can be easily modifiable to solve other real-time inspection/sorting problems. Three wavelengths at 517 nm, 565 nm and 802 nm were selected for real-time fecal detection imaging. The fecal detection algorithm was based on dual band ratios of 565nm/517nm and 802nm/517nm followed by thresholding. The software architecture was based on a ping pong memory and a circular buffer for the multitasking of image grabbing and processing. The software was written in Microsoft Visual C++. An image-based internal triggering (i.e. polling) algorithm was developed to determine the start and end positions of birds. Twelve chickens were used for testing the imaging system at two different speeds (140 birds per minute and 180 bird per minute) in a pilot-scale processing line. Four types of fecal materials (duodenum, ceca, colon and ingesta) were used for the evaluation of the detection algorithm. The software grabbed and processed multispectral images of the dimension 118 (line scans) x 512 (height) x 3 (bands) pixels obtained from chicken carcasses moving at the speed up to 180 birds per minute (a frame rate 286 Hz). Intensity calibration, detection algorithm, displaying and saving were performed within the real-time deadlines.

Citation Download Citation

Seung Chul Yoon, Bosoon Park, Kurt C. Lawrence, William R. Windham, and Gerald W. Heitschmidt "Development of real-time line-scan hyperspectral imaging system for online agricultural and food product inspection", Proc. SPIE 7676, Sensing for Agriculture and Food Quality and Safety II, 76760J (20 April 2010); https://doi.org/10.1117/12.850460

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