Early detection of apple bruises on different background colors using hyperspectral imaging

Abstract The potentials of a hyperspectral imaging system were investigated for early detection of bruises on ‘McIntosh’ apples. A hyperspectral imaging system was developed based on a spectral region between 400 and 1000 nm. Partial least squares method and stepwise discrimination analysis were used for data dimensionality reduction and selecting the effective wavelengths. Three effective wavelengths in the near infrared region (750, 820, 960 nm) were selected to realize multispectral imaging tests. The classification results indicated that the bruised apples were successfully distinguished from the sound apples. The accuracy of the system is superior to detect bruise after 1 h of bruising.

[1]  C. Jun,et al.  Performance of some variable selection methods when multicollinearity is present , 2005 .

[2]  Jack D. Wilson,et al.  A Model Study of Alternative Ventilation Systems For a Broiler House , 1974 .

[3]  Mitsuji Monta,et al.  Application of NIR-color CCD camera to Eggplant Grading Machine , 2005 .

[4]  Renfu Lu,et al.  Detection of bruises on apples using near-infrared hyperspectral imaging , 2003 .

[5]  Weikang Gu,et al.  Computer vision based system for apple surface defect detection , 2002 .

[6]  Y. R. Chen,et al.  Detection of Defects on Selected Apple Cultivars Using Hyperspectral and Multispectral Image Analysis , 2002 .

[7]  Moon S. Kim,et al.  DETECTION OF SKIN TUMORS ON CHICKEN CARCASSES USING HYPERSPECTRAL FLUORESCENCE IMAGING , 2004 .

[8]  Daniel E. Guyer,et al.  APPLE SORTING USING ARTIFICIAL NEURAL NETWORKS AND SPECTRAL IMAGING , 2002 .

[9]  Kurt C. Lawrence,et al.  Hyperspectral Image Classification for Fecal and Ingesta Identification by Spectral Angle Mapper , 2004 .

[10]  M. Destain,et al.  Defect segmentation on 'Jonagold' apples using colour vision and a Bayesian classification method , 1999 .

[11]  D. E. Chan,et al.  Development of Hyperspectral Imaging Technique for the Detection of Chilling Injury in Cucumbers; Spectral and Image Analysis , 2006 .

[12]  Reyer Zwiggelaar,et al.  Use of Spectral Information and Machine Vision for Bruise Detection on Peaches and Apricots , 1996 .

[13]  O. Dahlman,et al.  Chemical compositions of hardwood and softwood pulps employing photoacoustic Fourier transform infrared spectroscopy in combination with partial least-squares analysis. , 2002, Analytical chemistry.

[14]  D. L. Peterson,et al.  Performance of a System for Apple Surface Defect Identification in Near-infrared Images , 2005 .

[15]  K. Chao,et al.  Chicken Heart Disease Characterization by Multi-spectral Imaging , 2001 .

[16]  Tudor I. Oprea,et al.  An automated PLS search for biologically relevant QSAR descriptors , 2004, J. Comput. Aided Mol. Des..

[17]  Moon S. Kim,et al.  Hyperspectral Imaging for Detecting Defect on Apples , 2005 .

[18]  Hamid R. Arabnia,et al.  Apple classification based on surface bruises using image processing and neural networks , 2002 .

[19]  Giovanni Attolico,et al.  Non-destructive grading of peaches by near-infrared spectrometry , 2004 .

[20]  Rainer Künnemeyer,et al.  Method of Wavelength Selection for Partial Least Squares , 1997 .

[21]  Yang Tao,et al.  Building a rule-based machine-vision system for defect inspection on apple sorting and packing lines , 1999 .

[22]  J. Abbott,et al.  NEAR-INFRARED DIFFUSE REFLECTANCE FOR QUANTITATIVE AND QUALITATIVE MEASUREMENT OF SOLUBLE SOLIDS AND FIRMNESS OF DELICIOUS AND GALA APPLES , 2003 .

[23]  James A. Throop,et al.  Quality evaluation of apples based on surface defects: development of an automated inspection system , 2005 .

[24]  M. Destain,et al.  Development of a multi-spectral vision system for the detection of defects on apples , 2005 .

[25]  Alan M. Lefcourt,et al.  A novel integrated PCA and FLD method on hyperspectral image feature extraction for cucumber chilling damage inspection , 2004 .

[26]  Roy B. Dodd,et al.  Assessing Nitrogen Content of Golf Course Turfgrass Clippings Using Spectral Reflectance , 2004 .

[27]  U. M. Peiper,et al.  A Spectrophotometric Method for Detecting Surface Bruises on "Golden Delicious" Apples , 1994 .

[28]  Gerrit Polder,et al.  Hyperspectral image analysis for measuring ripeness of tomatoes. , 2000 .

[29]  Jasper G. Tallada,et al.  NIR Hyperspectral Imaging for Measurement of Internal Quality in Strawberries , 2005 .

[30]  Bosoon Park,et al.  Simple Algorithms for the Classification of Visible/Near-Infrared and Hyperspectral Imaging Spectra of Chicken Skins, Feces, and Fecal Contaminated Skins , 2003, Applied spectroscopy.

[31]  Moon S. Kim,et al.  Development of hyperspectral imaging technique for the detection of chilling injury in cucumbers , 2004, SPIE Optics East.

[32]  Renfu Lu,et al.  MODELING MULTISPECTRAL SCATTERING PROFILES FOR PREDICTION OF APPLE FRUIT FIRMNESS , 2005 .

[33]  P. Williams,et al.  Near-Infrared Technology in the Agricultural and Food Industries , 1987 .

[34]  Josse De Baerdemaeker,et al.  Bruise detection on ‘Jonagold’ apples using hyperspectral imaging , 2005 .

[35]  Xiaoyang Gao,et al.  Non-destructive apple bruise on-line test and classification with Raman spectroscopy , 2003 .

[36]  Moon S. Kim,et al.  Development of hyperspectral imaging technique for the detection of apple surface defects and contaminations , 2004 .

[37]  R. Lu.  Multispectral imaging for predicting firmness and soluble solids content of apple fruit , 2004 .