激光与光电子学进展, 2016, 53 (4): 041001, 网络出版: 2016-03-25   

基于RGB 颜色模型的红富士苹果表皮红色区域检测 下载: 836次

Detection of Red Region of Fuji Apple Based on RGB Color Model
作者单位
江南大学轻工过程先进控制教育部重点实验室, 江苏 无锡 214122
摘要
水果的颜色是水果分级的重要依据,影响着消费者的购买欲望。研究了一种基于RGB 颜色模型的红富士苹果表皮红色区域检测算法。通过苹果RGB 图像的光照补偿,降低光照变化和不均匀性带来的影响。在此基础上,计算各像素R、G、B 分量的G/B 和R/G 比值,通过训练获得其分割阈值,实现苹果图像和背景的准确分割。最后用超红-超绿阈值分割法检测分割后的苹果图像的红色区域并计算其面积。实验结果表明:基于RGB 颜色空间的红富士苹果表皮红色区域检测算法能够准确地检测出果皮表面的红色区域,满足红富士苹果颜色等级检测的需要。
Abstract
Color of fruits is an important index for the classification of fruits, which will affect consumers′ purchase desire. An algorithm based on RGB color model is studied to detect the red area of Fuji apple. The light compensation of image is used to reduce the effect of illumination change and nonuniformity of light source. Two parameters of R/G and G/B in RGB image are calculated, and the thresholds of these two parameters are obtained by using training samples to achieve accurate segmentation for apple and background. The excess red minus excess green threshold segmentation method is applied to detect and calculate the red region of apple surface. The experimental results show that the algorithm based on RGB color model is able to accurately detect the red area of the apple surface. The algorithm can meet the requirement of color grading detection of Fuji apples.
参考文献

[1] 刘燕德. 水果糖度和酸度的近红外光谱无损检测研究[D]. 杭州: 浙江大学, 2006: 1-15.

    Liu Yande. Study on Methods of Nondestructive Measurement of Sugar Content and Acidity in Fruits Using Near-Infrared Spectroscopy[D]. Hangzhou: Zhejiang University, 2006: 1-15.

[2] 刘鹏, 屠康, 潘磊庆, 等. 基于模糊机器视觉聚类的柿果表面缺陷识别研究[J]. 光学学报, 2009, 29(s2): 138-144.

    Liu Peng, Tu Kang, Pan Leiqing, et al.. Persimmon’s surface defect recognition based on machine vision fuzzy clustering [J]. Acta Optica Sinica, 2009, 29(s2): 138-144.

[3] 韩东海, 王加华. 水果内部品质近红外光谱无损检测研究进展[J]. 中国激光, 2008, 35(8): 1123-1131.

    Han Donghai, Wang Jiahua. Review of nondestructive measurement of fruit quality by means of near infrared spectroscopy [J]. Chinese J Lasers, 2008, 35(8): 1123-1131.

[4] Mizushima A, Lu R. A low- cost color vision system for automatic estimation of apple fruit orientation and maximum equatorial diameter[J]. Transactions of the ASABE, 2013, 56(3): 813-827.

[5] Warner G. Super-efficient picking system[J]. Good Fruit Grower, 2009, 60(2): 28-29.

[6] Zhou J, Yin H, Liu J, et al.. Method of image fusion for apple surface quality detection[C]. International Conference on Automatic Control & Artificial Intelligence, 2012: 1339-1342.

[7] Bennedsen B S, Peterson D L, Tabb A. Identifying defects in images of rotating apples[J]. Computer and Electronics in Agriculture, 2005, 2(48): 92-102.

[8] Wachs J P, Stern H I, Burks T. Low and high-level visual feature-based apple detection from multi-modal images[J]. Precision Agriculture, 2010, 11(6): 717-735.

[9] 周薇, 刘刚, 马晓丹, 等. 不同生长时期果树多源图像的配准方法研究[J]. 光学学报, 2014, 34(2): 0215001.

    Zhou Wei, Liu Gang, Ma Xiaodan, et al.. Study on multi-image registration of apple tree at different growth stages[J]. Acta Optica Sinica, 2014, 34(2): 0215001.

[10] 李庆中, 张漫, 汪懋华. 基于遗传神经网络的苹果颜色实时分级方法[J]. 中国图像图形学报, 2000, 5(9): 779-784.

    Li Qingzhong, Zhang Man, Wang Maohua. Real-time apple color grading based on genetic neural network[J]. Journal of Image and Graphics, 2000, 5(9): 779-784.

[11] 冯斌, 汪懋华. 基于颜色分形的水果计算机视觉分级技术[J]. 农业工程学报, 2002, 18(2): 141-144.

    Feng Bin, Wang Maohua. Computer vision classification of fruit based on fractal color[J]. Transactions of the CSAE, 2002, 18(2): 141-144.

[12] 饶秀勤, 应义斌. 水果按表面颜色分级的方法[J]. 浙江大学学报(工学版), 2009, 43(5): 869-871.

    Rao Xiuqin, Ying Yibin. Grading a fruit by its surface color[J]. Journal of Zhejiang University (Engineering Science), 2009, 43(5): 869-871.

[13] Mendoza F, Dejmek P, Aguilera J M. Calibrated color measurements of agricultural foods using image analysis[J]. Postharvest Biology and Technology, 2006, 41(3): 285-295.

[14] 李江波, 黄文倩, 张保华. 类球形水果表皮颜色变化校正方法研究[J]. 农业机械学报, 2014, 45(4): 226-230.

    Li Jiangbo, Huang Wenqian, Zhang Baohua. Correction algorithm of lighting non- uniformity on spherical fruit[J]. Transactions of the Chinese Society for Agricultural Machinery, 2014, 45(4): 226-230.

[15] 付鹏. 基于机器视觉的苹果检测与识别关键技术研究[D]. 杨凌: 西北农林科技大学, 2012: 5-12.

    Fu Peng. Research of the Key Technology of Apple Detection and Recognition Based on Machine Vision[D]. Yangling: Northwest A & F University, 2012: 5-12.

[16] Andris H L, Crisosto C. Improvement of ′Fuji′ apple color and fruit size using reflective materials[J]. Hortscience, 1995, 30 (4): 787.

[17] 饶秀勤. 基于机器视觉的水果品质实时检测与分级生产线的关键技术研究[D]. 杭州: 浙江大学, 2007: 2-18.

    Rao Xiuqin. Real-Time Inspection Technology of Fruit Quality Using Machine Vision[D]. Hangzhou: Zhejiang University, 2007: 2-18.

[18] 沈宝国, 魏新华, 尹建军. 基于最小外接圆法的苹果直径检测技术[J]. 农机化研究, 2011, 33(12): 131-134.

    Shen Baoguo, Wei Xinhua, Yin Jianjun. Apple diameter detection based on minimum circumcircle method[J]. Journal of Agricultural Mechanization Research, 2011, 33(12): 131-134.

[19] 王建, 黎绍发. 基于苹果着色面积的计算机视觉分级技术研究[J]. 计算机工程与设计, 2008, 29(14): 3813-3814.

    Wang Jian, Li Shaofa. Study on computer vision grading based on apple coloration area[J]. Computer Engineering and Design, 2008, 29(14): 3813-3814.__

[20] Meyer G E, Neto J C. Verification of color vegetation indices for automated crop imaging applications[J]. Computer and Electronics in Agriculture, 2008, 63(2): 282-293.

[21] Hsu R L, Abdel-Mottaleb M, Jain A K. Face detection in color images[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002, 24(5): 696-706.

[22] Wang C, Ma K K. Feature histogram equalization for feature contrast enhancement[J]. Journal of Visual Communication and Image Representation, 2015, 26: 255-264.

[23] 陈莹, 朱明, 李兆泽. 基于高斯混合模型的遥感数字图像增强[J]. 中国激光, 2014, 41(12): 1209002.

    Chen Ying, Zhu Ming, Li Zhaoze. Remote sensing digital image enhancement based on Gaussian mixture modeling[J]. Chinese J Lasers, 2014, 41(12): 1209002.

[24] 赵文达, 赵建, 赵凡, 等. 双峰高斯函数规定化的变分红外图像增强[J]. 中国激光, 2014, 41(3): 0309002.

    Zhao Wenda, Zhao Jian, Zhao Fan, et al.. Variable infrared image enhancement of bimodal Gaussian function specification [J]. Chinese J Lasers, 2014, 41(3): 0309002.

[25] 周渝人, 耿爱辉, 王莹, 等. 基于对比度增强的红外与可见光图像融合[J]. 中国激光, 2014, 41(9): 0909001.

    Zhou Yuren, Geng Aihui, Wang Ying, et al.. Contrast enhanced fusion of infrared and visible images[J]. Chinese J Lasers, 2014, 41(9): 0909001.

[26] 黄思婕, 陈凡胜, 廖星星. 一种基于多次曝光的大动态范围图像融合方法[J]. 中国激光, 2014, 41(s1): s109009.

    Huang Sijie, Chen Fansheng, Liao Xingxing. A high dynamic range fusion method based on multi-exposure imaging[J]. Chinese J Lasers, 2014, 41(s1): s109009.

黄兆良, 朱启兵. 基于RGB 颜色模型的红富士苹果表皮红色区域检测[J]. 激光与光电子学进展, 2016, 53(4): 041001. Huang Zhaoliang, Zhu Qibing. Detection of Red Region of Fuji Apple Based on RGB Color Model[J]. Laser & Optoelectronics Progress, 2016, 53(4): 041001.

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