提高彩色视觉测量对比度技术研究
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摘要
视觉测量作为一种非接触测量方法已经得到了广泛的应用,随着数字影像与光源设备硬件的进步和数学与计算机图像处理方法软件的发展,附有色彩信息的视觉测量技术开始受到更多的关注,相对于灰度视觉方式具有更丰富的信息,但是彩色视觉测量在工业应用上仍然较少。本文搭建了具有彩色照明光源和工业彩色相机的视觉测量系统,研究了视觉测量系统的正确显色方法,用于物体的颜色测量,研究了具有彩色信息的视觉测量理论和方法,用于提高检测目标的图像对比度。主要研究内容包括以下几方面:
     针对颜色测量与彩色图像采集对光源照明的要求:良好的多波段混光性,近距离照明的辐照均匀性。提出了一种间接照明的光源照明方式,利用多波段的LED阵列与高漫反射率的半球形内表面实现均匀照明,根据LED的朗伯体特性和高漫反射表面的双向分布函数构建了光源的数学模型,通过实测均匀度以及实拍的图像论证了理论模型的正确性与混光性的实现程度。搭建了一套基于此彩色照明光源和工业彩色相机的视觉测量系统,实现了彩色光源各个波段单独控制并且亮度256级数字可调。
     研究了彩色照明光源的色度学特性。通过与标准D65光源对比,三基色分量R:G:B=254:237:90时的色温和色度坐标最接近于D65光源,此时的颜色显现能力最好,光源的色彩饱和度更高,色彩表现更加丰富。相关色温变化范围宽泛,平均颜色复现误差也处于CIE规定的较优显示效果区域。针对采集到的彩色图片受相机的光谱响应函数和光源的影响,目标的颜色可能与物体真实的颜色存在一些差异,采用了多项式回归的方法分别在D65光源和LED阵列光源拍摄的图片进行校正,在不同颜色空间sRGB和CIEL*a*b*进行校正对比,分析了两种空间的图像显示、校正步骤以及校正精度等,选择了最为合适的颜色空间进行校正,并对一实际拍得的图片进行了颜色校正,效果良好。
     研究了最优波段光源照明方法用于提高目标的颜色对比度,借鉴彩色滤光方式,通过测量材料表面的反射函数,利用偏最小二乘法建立了数学模型,VIP得分为波段选择的最要依据,选取了能够提高检测表面对比度的三个波段间隔,实验结果证实了方法的有效性。
     利用光的偏振特性提高目标的颜色对比度,在工业电路板检测时,通过旋转线偏振片,获取0度、45度、90度不同相位图像,计算得到了偏振度和偏振相位图像后,与彩色视觉测量系统获取的彩色信息结合,分别在RGB和HSI空间进行了图像融合,相对于原来的图像,融合后图像中目标的颜色对比度显著提高,并且不受光照过暗、不均的影响。
Currently vision measurement has been widely used as a non-contact measurement method. With the development of digitized video, illumination hardware equipment, mathematics and image processing software, the technology of vision measurement with color information has been given serious attention. Compared to grayscale vision, color vision measurement has abundant information, but it is still used less for industry application. The vision measurement system with color illumination and color CCD was constructed. The method of coloration for our vision measurement system was performed to measurement the color of object. The method of color vision measurement was studied for enhancing the contrast of detected object. The main research contents are shown as follows:
     For color measurement and image acquisition, well multiple-wavelength color mixing characteristic and illumination uniformity of near-field distance are needed. This paper presents an indirect method for vision measurement system. Multiple-wavelength LED arrays and sphere inner surface with high reflectance were used to realize the uniform illumination. Using the Lambertian characteristic and Bi-directional Reflectance Distribution Functions (BRDF) of the sphere’s inner surface, a mathematically simulated algorithm is developed. The uniformity of color illumination and the experiment images were used to verify the validity of simulated algorithm and the mixing results. Then the color vision measurement system was constructed by color illumination and color CCD. Each wavelength of LED intensity was independent controlled, and can be adjusted from 0 to 255.
     The colorimetric property of color illumination was studied. Compared to standard D65 illumination, chromaticity coordinates and correlated color temperature of white balance R:G:B=254:237:90 are close to D65 illumination. Color vision light source has a large range for adjusting the correlated color temperature and has better ability of color display. The ability of color reproduction reaches better result of color reproduction.
     The captured images of color vision system were influenced by spectral response functions of camera and the illumination. The color of object is different from the truth color. The method of polynomial regression was used for color correction of color illumination and D65illumination. The precision of correction, image display and correction procedure were compared in sRGB and CIEL*a*b* color space. Then the sRGB color space was selected. A real captured image was used for color correction, and the color of object is closed to the truth color.
     Wavelength intervals selection of illumination was used for enhancing the contrast of image. The reflectance functions of material surface were measured. The Partial least squares(PLS) was used for building the mathematic model, the VIP scores were used for selecting the effective wavelength intervals. Three wavelength intervals were used for color illumination. The experiment results show the usefullness of this method.
     The polarization property of light is useful for color vision measurement system. The fusion of polarization and color image was used for enhancing the contrast of image. For detecting the industry circuit wafer, the 0, 45, and 90 indicate the orientation of the polarizer in degrees when each specific image was taken. The Degree-of-polarization and Phase-polarization images were obtained. Then these two images and color image were fused into one image in RGB and HSI color space. Compared to original image, the fusion image contrast was enhanced, and was not influenced by the intensity, uniformity of illumination.
引文
[1] T.Linmi, X.Guangyou. Color in machine vision and its application. Chinese Science Bulletin.2001.46(17):1411-1421
    [2] S. Ratnasingam, S. Collins, J. Hernández-Andrés. Optimum sensors for color constancy in scenes illuminated by daylight. Journal of the optical society of America A-optics image science and vision. 2010. 27(10):2198-2207
    [3]S.K.Kopparapu. Lighting design for machine vision application. Image and vision computing. 2006. 24: 720-726
    [4] A.A.Kassim, M.A.Mannan, Z.Mian. Texture analysis methods for tool condition monitoring. 2007. 25:1080-1090
    [5] S. Mersch. Overview of machine vision lighting techniques, Proceedings of SPIE 1987. 728 :36–38
    [6]林岳,叶烈武,刘文杰等.二分法优化计算LED光源相关色温.光学学报.2009.29(10):2791-2794
    [7]周印华,汤英文,饶建平等.光增强湿法刻蚀si衬底垂直结构GaN基LED的出光效率.光学学报. 29(1):252-255.
    [8] I.Moreno,M.A.Alejo,R.I.Tzonchev. Designing light-emitting diode arrays for uniform near-field irradiance. Applied optics. 2006. 45(10): 2265-2272
    [9]丁毅,顾培夫.实现均匀照明的自由曲面反射器.光学学报.2007.27(3):540-544
    [10] Y.Ding,X.Liu,Z.Zheng et.al. Freeform LED lens for uniform illumination. Optics Express . 2008.16(17) :12958-12966
    [11] C. Sun, W. Chien, I. Moreno et.al. Analysis of the far-field region of LEDs. Optics Express.2008.17(16):13918-13927
    [12] I.Moreno. Design of LED spherical lamps for uniform far-field illumination. Proc.of SPIE 2006.6046:60462E 1-7
    [13] I.Moreno. Configurations of LED arrays for uniform illumination.Proc.of SPIE2004. 5622:713-718
    [14] I.Moreno,J.Munoz,R.Ivanov. Uniform illumination of distant targets using a spherical light-emitting diode array. Optical Engineering . 2007.46(3):033001 1-7.
    [15] I.Moreno,M.A.Alejo,R.I.Tzonchev. Designing light-emitting diode arrays for uniform near-field irradiance. Applied optics. 2006. 45(10):2265-2272
    [16] A.J.W.Whang,Y.Y.Chen,Y.T.Teng. Designing uniform illumination systems by surface-Tailored Lens and Configurations of LED Arrays. Journal of display technology .2009.5(3):94-103
    [17] S.Yi, R.M.Haralick,L.G. Shapiro. Optimal sensor and light source position for machine vision. Computer vision and image understanding. 1995. 16(1):122-137
    [18]赵星,方志良,宋丽培等.数字光背投电视色度学特性的研究.光子学报,2007,36(2):355-358.
    [19]赵星,方志良,母国光.投影光源的色度学特性研究.物理学报,2007,56(5):2537-2540
    [20]宋功保,彭同江,万朴等. TiO2/白云母纳米复合材料的的色度学研究[J].物理学报,2002,57(7):1575-1580
    [21]陈定安,沈里,张家雨等.胶体CdSe量子点的色度学特性研究. 2007. 56(11):6340-6344
    [22]李素文,谢品华,刘文清等.发光二极管在差分吸收光谱系统中的应用研究.物理学报.2007,57(3):1963-1967
    [23] King T L, Susan B, Roderick L S et.al. Novel fused-LEDs devices as optical sensors for colorimetric analysis. Talanta. 2004. 63:167-173
    [24] Fryc I, Brown S W, Eppeldauer G P, Ohno Y. A Spectrally Tunable Solid-State Source for Radiometric, Photometric and Colorimetric Applications. Proc.SPIE. 2004. 5530:150-159.
    [25] I. Fryc, E. Czech, Spectral correction of the measurement CCD array. 2002. Optical Engineering. 41(10):2402-2406
    [26] M. Wolski, C. A. Bouman, J. P. Allebach et.al . Optimization of sensor response functions for colorimetry of reflective and emissive objects. IEEE transactions on imaging precessing. 1996.5(3):507-517
    [27] D.Corell, H. Ou, C.Dam-Hansen,P.Petersen, D.Friis. Light Emitting Diodes as an alternative ambient illumination source in photolithography environment. Optics Express. 2009. 17(20):17923-17302
    [28]史玲娜,潘英俊,张洁等.基于光栅光调制器的照明光源的显示特性研究[J].光学学报,2010,30(2):531-536
    [29] X.Wang, D.Zhang. An Optimized Tongue Image Color Correction Scheme. IEEE Transactions on Information Technology in Biomedicine.2010.14(6): 1355-1364
    [30] W.Li., M.Soto-Thompson, U.Gustafsson. A new image calibration system in digital colposcopy. Optics Express. 2006.14(26):12888-12901
    [31] M. J. Vrhel, H. J. Trussell. Color Device Calibration: A Mathematical Formulation. IEEE Transactions on image processing. 1999.8(12):1796-1806
    [32] M.Shi, G. Healey. Using reflectance models for color scanner calibration. Journal of the optical society of America A-optics image science and vision. 2002. 19(4): 645-656
    [33] G.Hong., M.R.Luo,P.Rhodes. A Study of Digital Camera Colorimetric Characterization Based on Polynomial Modeling. Color research and application. 2001.26(1):76-84
    [34]刘关松,吕嘉雯,徐建国等.监督颜色校正方法研究.计算机学报. 2003.26(4): 502-506
    [35] Y.C.Chang, J.F.Reid. RGB Calibration for Color Image Analysis in Machine Vision. IEEE Transactions on image processing. 1996. 5(10):1414-1422
    [36] W.Kao, S.Wang, C.Kao et.al. Color Reproduction for Digital Imaging Systems. IEEE International Symposium on Circuits and System. 2006:4599-4602
    [37]C. Saint-Pierre, J. Boisvert, G. Grimard et.al. Detection and correction of specular reflections for automatic surgical tool segmentation in thoracoscopic images. Machine Vision and Applications. 2007. 27(10):642-652
    [38]L.Chiu, F. C.Fuh. Dynamic Color Restoration Method in Real Time Image System Equipped With Digital Image Sensors. Journal of the Chinese Institute of Engineers. 2010.33(2).:243-250
    [39]Z. Kosztyán, G. Eppeldauer, J. Schanda. Matrix-based color measurement corrections of tristimulus colorimeters. Applied Optics. 2010.49(12):2288-2301
    [40]Y.V.Haeghen, J. Naeyaert, I.Lemahieu et.al. An Imaging System with Calibrated Color Image Acquisition for Use in Dermatology. IEEE Transactions on medical imaging. 2000.19(7): 722-730
    [41]V. Cheung, S. Westland, D. Connaha et.al. A comparative study of the characterization of colour cameras by means of neural networks and polynomial transforms. Coloration Technology. 2004.120:19-25
    [42] H.M.G. Stokman T.Gevers.Color Measurement by imaging Spectrometry. Computer Vision and Image Understanding . 2000.79:236-249
    [43] K.K?l?c, B.Onal-Ulusoyb, I.H. Boyac?. A novel method for color determination of edible oils in L*a*b* format. European Journal of Lipid Science and Technology. 2007.109:157-164
    [44] F. Ding, Y. R. Chen, and K. Chao. Two-waveband color-mixing binoculars for the detection of wholesome and unwholesome chicken carcasses: a simulation. Applied Optics.2005.44: 5454–5462.
    [45] D.Fujian, C.Yud-Ren, C.Kuanglin, M. Kim. Three-color mixing for classifying agricultural products for safety and quality. Applied Optics. 2006.45(15):3516-3526
    [46] D.Fujian, C.Yud-Ren, C.Kuanglin, D.Chan. Two-color mixing for classifying agricultural products for safety and quality. Applied Optics. 2006.45(4):668-677
    [47] M. J. Vrhel , H. J. Trussell. Optimal color filters in the presence of noise. IEEE transactions on imaging precessing. 1995.4(6):814-823
    [48] M. J. Vrhel ,H. J. Trussell, J.Bosch. Design and realization of optimal color filters for multi-illuminant color correction. Journal of Electronic Imaging. 1995.4(1):6-14
    [49] P.Vora, H.J.Trussell. Mathematical methods for the design of color scanning filters. IEEE transactions on imaging precessing. 1997.6(2):312-320.
    [50] N.Tsumura, T.Tanaka, H.Haneishi, Y.Miyake. Optimal design of mosaic color filters for the improvement of image quality in electronic endoscopes. Optics Communications. 1998. 145:27–32
    [51] D.Ng, J.P.Allebach. A subspace matching color filter design methodology for a multispectral imaging system. IEEE transactions on imaging precessing. 2006.15(9):2631-26432
    [52]M.Hauta-Kasari, K. Miyazawa, S. Toyooka et.al. spectral vision system for measuring color images .”J.Opt.Soc.Amer. 1999.16(10):2352-2362
    [53] W.Wu, J .P.Allebach. Imaging colorimetry using a digital camera. Journal of image science and technology. 2000. 47(4): 531-542
    [54] F.H.Imai, R.S.Berns, D.Tzeng. A comparative analysis of spectral reflectance estimated in various spaces using a trichromatic camera system. Journal of image science and technology. 1995.44(4),280-287.
    [55] D.Ng,J .P.Allebach, M. Analoui et.al. Non-contact imaging colorimeter for human tooth color assessment using a digital camera. Journal of image science and technology. 2003.47(6):531-542
    [56] S.Tominaga and T.Yamamoto. Metal-Dielectric Object Classification by Polarization Degree Map. Proc. IEEE 19th International Conference on Pattern Recognition (ICPR). 2008
    [57] J.Fu, H.J. Caulfield. Applying color discrimination to polarization discrimination in images. Optics communications.2007.272:362-366
    [58] Y.Zhao, L.Zhang, D.Zhang. Object separation by polarimetric and spectral imagery fusion. Computer vision and image understanding. 2009.113:855-866
    [59] H.Chen, L.B.Wolff. Polarization phase-based method for material classification in computer vision. 1998. 28(1):73-83
    [60] Wolff, L.B. Polarization-based material classification from specular reflection. IEEE Transactions on Pattern Analysis and Machine Intelligence. 1990. 12(11) : 1059–1071
    [61] S.Lin, K.M. Yemelyanov. Separation and contrast enhancement of overlapping cast shadow components using polarization. Optics express.2006.14(16):7099-7108
    [62] F.Goudail, A.Bénière. Optimization of the contrast in polarimetric scalar images. Optics letters.2009. 34(9).1471-1473
    [63] M.W.Hyde, J.D.Schmidt, M.J.Havrilla et.al.Enhanced material classification using turbulence-degraded polarimetric imagery. Optics letters. 2010 . 35(21) : 3601- 3603
    [64] S.A?nouz1, J.Zallat, A.Martino. Physical interpretation of polarization-encoded images by color preview. Optics express.2006.14(13):5916-5927
    [65] N.Gupta, L.J.Denes, M.Gottlieb. Object detection with a field-portable spectropolarimetric imager. Applied optics. 2001.40(36):6626-6632
    [66] G.A.Atkinson, E.R.Hancock.Recovery of surface orientation from diffuse polarization. IEEE transactions on image processing. 2006. 15(6):1653-1664
    [67]谢斌,项志宇,潘华东等.基于偏振信息的水体障碍物检测方法.浙江大学学报工学版.2007.41(11):1834-1838
    [68] P.Terrier,V.Devlaminck,J.M.Charbois. Segmentation of rough surfaces using a polarization imaging system. Opt. Soc. Am. A.2008.25(2):423-430
    [69] L.B.Wolff. Polarization camera for computer vision with a beam splitter. Opt. Soc. Am. A.1994.11(11):2935-2945
    [70]L.B.Wolff, T.A.Mancini,P.Pouliquen et.al. Liquid Crystal Polarization Camera. IEEE transactions on robotics and automation.1997.13(2):195-203
    [71] J.S.Tyo, D.L.Goldstein, D.B. Chenault. Review of passive imaging polarimetry for remote sensing applications. 2006.45(22):5453-5469
    [72] A. C. M. Oliveira, M. O. Balaban. Comparison of a Colorimeter with a Machine Vision System in Measuring Color of Gulf of Mexico Sturgeon Fillets. Applied Engineering in Agriculture.2006.22(4):583-587
    [73] M.Kutila,J.Viitanen,A.Vattulainen. Scrap Metal Sorting with Colour Vision and Inductive Sensor Array. Proceedings of CIMCA-IAWTIC.2005.
    [74] C.Boukouvalas, J.Kittler, R.Marik et.al. Automatic color grading of ceramic tiles using machine vision. IEEE Transactions on industrial electronics. 1997. 44(1):132-135
    [75] C.Boukouvalas, J.Kittler, R.Marik et.al. Color Grading of Randomly Textured Ceramic Tiles Using Color Histograms. IEEE Transactions on industrial electronics.1999.46(1):219-226
    [76] S.Kukkonen, H. Kalviainen, J. Parkkinen. Color features for quality control in ceramic tile industry. Optical engineering. 2001. 40(2):170-177
    [77] X.Xianghua, M.Mirmehdi, B.Thomas. Colour tonality inspection using eigenspace features. Machine Vision and Applications.2006.16(6):364-373
    [78] K.K?l?c, I.Hakki Boyac?, H.Ko¨ksel, I.Ku¨smenog?lu. A classification system for beans using computer vision system and artificial neural networks. Journal of Food Engineering.2007.78:897–904
    [79] M.J.Mortan, D.L.Williams, H.B.Hjorth et.al. Machine-smoking studies of cigarette filter color to estimate tar yield by visual assessment and through the use of a colorimeter. Regulatory Toxicology and Pharmacology. 56:321-331
    [80] J.Pospsil, J.Hrdy, J.H.Jr. Basic methods for measuring the reflectance color of iron oxides. Optik. 2007. 118:278-288
    [81] J. Lu, J.Tan, P. Shatadal, D.E.Gerrard. Evaluation of pork color by using computer vision. Meat Science.2000.56:57-60
    [82] K. Chen, X. Sun, Ch. Qin, X. Tang. Color grading of beef fat by using computer vision and support vector machine. Computers and Electronics in Agriculture . 2010. 70:27-32
    [83] D.Lee, J.Archibald, X.Guangming. Rapid Color Grading for Fruit Quality Evaluation Using Direct Color Mapping. IEEE Transactions on industrial electronics.2011.8(2):292-302
    [84] J.C. Noordam, G.W. Otten, A.J.M. Timmermans, B.H. van Zwol. High speedpotato grading and quality inspection based on a color vision system. Proc. SPIE 2006. 3966:206-217
    [85] W.Xuanyin, L.Dongtai, D.Weiyan. Surface grading of bamboo strips using multi-scale color texture features in eigenspace. Computers and Electronics in Agriculture.2010.73:91-98
    [86]罗玮,彭复员,柳健.彩色瓷砖的自动分类系统.华中科技大学学报.2001.29(3):79-81
    [87] Vriesenga, M., Healey, G., Peleg et.al. Controlling illumination color to enhance object discriminability. Proc. Int. Conf. on Computer Vision and Pattern Recognition CVPR.1992. :710~712
    [88] M. Vriesenga, G. Healey, J. Sklansky, K. Peleg. Colored illumination for enhancing discriminability in machine vision. Journal of Visual Communication and Image Representation. 1995.6(3):244~255
    [89] D.Carson, Y.Oriharab, J. Sorbic,D. Poundera. Detection of white restorative dental materials using an alternative light source. Forensic Science International.1996.88:163-168
    [90] H.M.Suen,J.F. Wang. Segmentation of uniform-coloured text from colour graphics background.IEEE Proc.Vision Image Signal Puocess.1997.144(6):317-322
    [91] Y.Lee,J.Kim,J.Ahn. Influence of the changes in the UV component of illumination on the color of composite resins. The Journal of Prosthetic Dentistry. 2007.97(6):375-380
    [92] R Seulin, F. Merienne, P. Gorria. Dynamic lighting system for specular surface inspection. The International Society for Optical Engineering. 2001
    [93]G.Salis, R.Seulin,O.Morel. Machine vision system for the inspection of reflective parts in the automotive industry. Proc.SPIE .2007.6503:1-9
    [94] N.Katafuchi, M.Sano, S.Ohara, M.Okudaira. A method for inspecting industrial parts surfaces based on an optics model. Machine Vision and Applications.2000.12: 170-176
    [95] G. Rosati, G.Boschetti, A.Biondi, A.Rossi. Real-time defect detection on highly reflective curved surfaces. Optics and Lasers in Engineering. 2009.47: 379-384
    [96] M.Dalla Valle, P.Gallina, A.Gasparetto. Mirror Synthesis in a Mechatronic System for Superficial Defect Detection. IEEE/ASME Transactions on Mechatronics. 2003. 8(3): 309-317
    [97] R.A. Boby, P.Sonakar, M. Singaperumal et.al. Identification of defects on highly reflective ring components and analysis using machine vision. 2011. 52: 317-233
    [98] D.Aluze, F.Merienne, C.Dumont et.al. Vision system for defect imaging, detection, and characterization on a specular surface of a 3D object. Image and Vision Computing.2002.20: 569–580
    [99] K.Khalili, P.Webb. The development and application of a multiple wavelength illumination technique for the vision-based process monitoring of aero-structureriveting. Machine Vision and Applications. 2007. 18: 73-83
    [100] D.Scribner, J.Schuler, P.Warren et.al. Infrared Color Vision: Separating Objects from Backgrounds. Proc.SPIE.1998. 3379, 2-13.
    [101]应义斌,景寒松,马俊福等.黄花梨品质检测机器视觉系统.农业机械学报.2000.31(2):113-115
    [102]俞晓磊,赵志敏,汪东华.棉结在线检测系统中的光源选择.中国激光.2008.35(5):788-791
    [103]王沈辉,陈树人,王新忠等.主动视觉中番茄定位特征照射光源的实验研究.农机化研究.2006.4:140-142
    [104]贾辉,李福田.硫酸钡漫反射板在250~400nm光谱辐射亮度标定中的应用研究.光谱学与光谱分析.2004.24(1):4-8
    [105]李聪,王咏梅,张仲谋.紫外光谱辐射定标中的漫反射板反射特性研究.光谱学与光谱分析.2008.28(4):865-869
    [106]梁海昱.彩色视觉测量应用及照明技术研究.[硕士学位论文].天津大学.2010
    [107]荆其诚,焦书兰.色度学.北京:科学出版社.1979. 92-100, 229-235, 252-256, 291-398
    [108] K.H. B?uml.Color appearance: effects of illuminant changes under different surface collections. Journal of the Optical Society of America A. 11(2):531-542
    [109] G.Sapiro. Color and Illuminant Voting. IEEE Transactions on pattern analysis and machine intelligence.1999.21(11):1210-1215
    [110] L. G.Corzo, J. A. Penaranda,P. Peer.Estimation of a fluorescent lamp spectral distribution for color image in machine vision. Machine Vision and Applications. 2005.16(5):306-311
    [111] H. Kauppinen, O. Silven. The effect of illumination variation on color-based wood defect classification. Proceedings of the 13th ICPR Volume 3, IEEE.1996 :828~832
    [112] K.M. Lee, W. Daley, Q. Li. Artificial color contrast for machine vision and its effects on feature detection. Advanced Intelligent Mechatronics. Proceedings IEEE/ASME International Conference on, 2005:219-224
    [113] H. D. Cheng, X. Cai, R. Min. A novel approach to color normalization using neural network. Neural Comput & Applic. 2009.18:237-247
    [114] W.L. Song,W.Wei, Y.Q.Liu. Novel Semiconductor Illumination Technique Based on Color Complementation. Second IEEE Conference on Industrial Electronics and Applications. 2007 :2036~2039
    [115]曲兴华,何滢,韩峰等.强反射复杂表面随机缺陷检测照明系统分析.光学学报,2003.23(5):547-551
    [116]G.ElMasry, N.Wang, C.Vigneault et.al. Early detection of apple bruises on different background colors using hyperspectral imaging. LWT- Food Science and Technology.2008.41:337-345
    [117] S.D.Osborne, R.B.Jordan. R.Künnemeyer. Method of wavelength selection for Partial Least Squares.The Analyst (chemistry). 2001.122: 1531-1537
    [118]王纪华,黄文江,劳彩莲等.运用PLS算法由小麦冠层反射光谱反演氮素垂直分布.光谱学与光谱分析.2007.27(7):1319-1322
    [119]M.Olah, C. Bologa, T.I.Oprea. An automated PLS search for biologically relevant QSAR descriptors. Journal of Computer-Aided Molecular Design .2004.18: 437-449
    [120]T.sun, H.Lin, H.Xu et.al. Effect of fruit moving speed on predicting soluble solids content of‘Cuiguan’pears (Pomaceae pyrifolia Nakai cv. Cuiguan) using PLS and LS-SVM regression.”Postharvest Biology and Technology, 51,86-90(2009)
    [121]杜振辉,齐汝宾,张慧敏等.近红外光谱定量检测丙烷和异丁烷.天津大学学报.2008.41(5):588-592
    [122]宋沙磊,李平湘,龚威.基于水稻高光谱遥感数据的PLS波长选择研究.武汉大学学报信息科学版.2010.35(2):220-223
    [123]淡图南,戴连奎.基于PLS投影分析的光谱波段选择方法.光谱学与光谱分析. 2009.29(2):351-354
    [124] R.Gosselin, D.Rodrigue, C. Duchesne. A bootstrap-VIP approach for selecting wavelength intervals in spectral imaging applications. Chemometrics and Intelligent Laboratory Systems. 2010.100:12-21
    [125] L.N?rgaard, A.Saudland, J.Wanger et.al. Interval partial least-squares regression (iPLS): a comparative chemometric study with an example from near-infrared spectroscopy. Applied spectroscopy. 2005.54:413-419
    [126]L.P.Brás, M.Lopes, A.P.Ferreira et.al. A bootstrap-based strategy for spectral interval selection in PLS regression. Journal of Chemometrics. 2008.22:695-700
    [127] B.G.Batchelor. Characterizing the illumination in an automated vision inspection work cell. Proc.SPIE.1999.3836:134-143
    [128] H.Lee, E.J.Breneman, C.P.schulte. Modeling lighting for computer color vision. IEEE transactions on pattern analysis and machine intelligence.1990.12(4):402-409
    [129] L.Eriksson, E.Johansson, N.Kettaneh-Wold et.al. Multi- and megavariate data analysis. Principles and Applications. Umetrics Academy, Umea.Sweden. 2001
    [130] T.H.Waterman. Polarization sensitivity. Handbook of Sensory Physiology. Vol. 7 ,Part 6b : Vision of Invertebrates. Berlin : SpringerVerlag , 1981:283– 463
    [131] Z.Jia, B.Wang, W.Liu et.al. An improved image acquiring method for machine vision measurement of hot formed parts. Journal of materials processing technology.2010.210:267-271
    [132] S.B.Dworkin, T.J.Nye. Image processing for machine vision measurement of hot formed parts. Journal of materials processing technology.2006.174:1-6
    [133] W.Liu, X.Jia, Z.jia et.al. Fast dimensional measurement method and experiment of the forgings under high temperature. Journal of materials processing technology.2011.211:237-244

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