Multispectral Method for Apple Defect Detection Using Hyperspectral Imaging System
ABSTRACT
Title of Document:
Multispectral Method for Apple Defect Detection using Hyperspectral Imaging System Tao Tao, Master of Science, 2011
Directed By:
Dr. Gang Qu, Associate Professor
Hyperspectral imaging is a non-destructive detection technology and a powerful analytical tool that integrates conventional imaging and spectroscopy to get both spatial and spectral information from the objects for food safety and quality analysis. A recently developed hyperspectral imaging system was used to investigate the wavelength between 530nm and 835nm to detect defects on Red Delicious apples. The combination of band ratio method and relative intensity method were developed in this paper, which using the multispectral wavebands selected from hyperspectral images. The results showed that the hyperspectral imaging system with the properly developed multispectral method could generally identify 95% of the defects on apple surface accurately. The developed algorithms could help enhance food safety and protect public health while reducing human error and labor cost for food industry.
MULTISPECTRAL METHOD FOR APPLE DEFECT DETECTION USING HYPERSPECTRAL IMAGING SYSTEM
By
TAO TAO
Thesis submitted to the Faculty of the Graduate School of the University of Maryland, College Park, in partial fulfillment of the requirements for the degree of Master of Science 2011
Advisory Committee: Dr. Gang Qu, Chair Dr. Moon Kim Dr. Robert Newcomb Dr. Chun Chieh Yang
© Copyright by Tao Tao 2011
Acknowledgements
I would like to thank the Environmental Microbiological and Food Safety Laboratory (EMFSL), Agricultural Research Service (ARS), United States Department of Agriculture and the Department of Electrical and Computer Engineering (ECE) at the University of Maryland, College Park (UMD) for sponsoring this work. I greatly acknowledge my advisor Dr. Gang Qu (ECE, UMD), who has supported my graduate studies. I am very thankful to Dr. Moon S. Kim (ARS, USDA),
Title of Document:
Multispectral Method for Apple Defect Detection using Hyperspectral Imaging System Tao Tao, Master of Science, 2011
Directed By:
Dr. Gang Qu, Associate Professor
Hyperspectral imaging is a non-destructive detection technology and a powerful analytical tool that integrates conventional imaging and spectroscopy to get both spatial and spectral information from the objects for food safety and quality analysis. A recently developed hyperspectral imaging system was used to investigate the wavelength between 530nm and 835nm to detect defects on Red Delicious apples. The combination of band ratio method and relative intensity method were developed in this paper, which using the multispectral wavebands selected from hyperspectral images. The results showed that the hyperspectral imaging system with the properly developed multispectral method could generally identify 95% of the defects on apple surface accurately. The developed algorithms could help enhance food safety and protect public health while reducing human error and labor cost for food industry.
MULTISPECTRAL METHOD FOR APPLE DEFECT DETECTION USING HYPERSPECTRAL IMAGING SYSTEM
By
TAO TAO
Thesis submitted to the Faculty of the Graduate School of the University of Maryland, College Park, in partial fulfillment of the requirements for the degree of Master of Science 2011
Advisory Committee: Dr. Gang Qu, Chair Dr. Moon Kim Dr. Robert Newcomb Dr. Chun Chieh Yang
© Copyright by Tao Tao 2011
Acknowledgements
I would like to thank the Environmental Microbiological and Food Safety Laboratory (EMFSL), Agricultural Research Service (ARS), United States Department of Agriculture and the Department of Electrical and Computer Engineering (ECE) at the University of Maryland, College Park (UMD) for sponsoring this work. I greatly acknowledge my advisor Dr. Gang Qu (ECE, UMD), who has supported my graduate studies. I am very thankful to Dr. Moon S. Kim (ARS, USDA),