Automatic detection of common surface defects on oranges using combined lighting transform and image ratio methods

[1]  R. R. Wolfe,et al.  Computer vision based system for quality separation of fresh market tomatoes , 1984 .

[2]  Q. Yang,et al.  Finding stalk and calyx of apples using structured lighting , 1993 .

[3]  Qingsheng Yang,et al.  Apple Stem and Calyx Identification with Machine Vision , 1996 .

[4]  T. G. Crowe,et al.  Real-time Defect Detection in Fruit — Part I: Design Concepts and Development of Prototype Hardware , 1996 .

[5]  T. G. Crowe,et al.  Real-time Defect Detection in Fruit — Part II: An Algorithm and Performance of a Prototype System , 1996 .

[6]  Y. Tao Spherical transform of fruit images for on‐line defect extraction of mass objects , 1996 .

[7]  Vincent Leemans,et al.  Defects segmentation on 'Golden Delicious' apples by using colour machine vision , 1998 .

[8]  Yang Tao,et al.  AN ADAPTIVE SPHERICAL IMAGE TRANSFORM FOR HIGH-SPEED FRUIT DEFECT DETECTION , 1999 .

[9]  Yang Tao,et al.  DUAL-CAMERA NIR/MIR IMAGING FOR STEM-END/CALYX IDENTIFICATION IN APPLE DEFECT SORTING , 2000 .

[10]  James A. Throop,et al.  Apple Orientation on Two Conveyors: Performance and Predictability Based on Fruit Shape Characteristics , 2001 .

[11]  José Blasco,et al.  Multispectral inspection of citrus in real-time using machine vision and digital signal processors , 2002 .

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

[13]  Yang Tao,et al.  DETECTING STEM AND SHAPE OF PEARS USING FOURIER TRANSFORMATION AND AN ARTIFICIAL NEURAL NETWORK , 2003 .

[14]  Vincent Leemans,et al.  A real-time grading method of apples based on features extracted from defects , 2004 .

[15]  Michael Recce,et al.  Video Grading of Oranges in Real-Time , 2004, Artificial Intelligence Review.

[16]  Josse De Baerdemaeker,et al.  Detecting Bruises on ‘Golden Delicious’ Apples using Hyperspectral Imaging with Multiple Wavebands , 2005 .

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

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

[19]  Bernard Gosselin,et al.  Stem and calyx recognition on ‘Jonagold’ apples by pattern recognition , 2007 .

[20]  Jiang Jia,et al.  テトラフルオロスチロール基を含むフッ化ポリ(アリーレンエーテルケトン)の紫外線フォトパターニングによる導波路デバイスの作製 , 2007 .

[21]  Zhu Bin,et al.  Three-dimensional shape enhanced transform for automatic apple stem-end/calyx identification , 2007 .

[22]  José Blasco,et al.  Citrus sorting by identification of the most common defects using multispectral computer vision , 2007 .

[23]  José Blasco,et al.  Computer vision detection of peel defects in citrus by means of a region oriented segmentation algorithm , 2007 .

[24]  G. Camps-Valls,et al.  Hyperspectral system for early detection of rottenness caused by Penicillium digitatum in mandarins , 2008 .

[25]  D. Bulanon,et al.  Classification of grapefruit peel diseases using color texture feature analysis , 2009 .

[26]  J. Qin,et al.  Detection of citrus canker using hyperspectral reflectance imaging with spectral information divergence , 2009 .

[27]  D. Bulanon,et al.  Spectral reflectance characteristics of citrus canker and other peel conditions of grapefruit. , 2009 .

[28]  Fernando López-García,et al.  Automatic detection of skin defects in citrus fruits using a multivariate image analysis approach , 2010 .