تشخیص و جداسازی گره و میانگره در ساقه‌های نیشکر به صورت برخط با کمک بینایی ماشین

Abbasgholipour, M., Omid, M., Keyhani, A. and Mohtasebi, S. 2011. Color image segmentation with genetic algorithm in a raisin sorting system based on machine vision in variable conditions. Expert Syst. Appl. 38, 3671–3678.

Brosnan, T. and Sun, D. W. 2002. Inspection and grading of agricultural and food products by computer vision systems – a review. Comput. Electron. Agric. 36, 193–213.

Brosnan, T. and Sun, D. W. 2004. Improving quality inspection of food products by computer vision – a review. J. Food Eng. 61, 3–16.

Du, C. J. and Sun, D. W. 2004. Recent developments in the applications of image processing techniques for food quality evaluation. Trends Food Sci. Tech. 15, 230–249.

Du, C. J. and Sun, D.W. 2006. Learning techniques used in computer vision for food quality evaluation: a review. J. Food Eng. 72, 39–55.

ElMasry, G., Cubero, S., Molt, E. and Blasco, J. 2012. In-line sorting of irregular potatoes by using automated computer-based machine vision system. J. Food Eng. 112, 60–68.

Gonzalez, R. C. Woods, R. E. and Eddins, S. L. 2009. Digital Image Processing Using MATLAB, vol. 2.

Hames, B. R., Thomas, S. R., Sluiter, A. D., Roth, C. J. and Templeton, D. W. 2003. Rapid biomass analysis. In: Biotech. Fuels Chem. Springer, pp. 5–16.

Hu, Z., Sykes, R., Davis, M. F., Charles Brummer, E. and Ragauskas, A. J. 2010. Chemical profiles of switchgrass. Bioresource Technol. 101, 3253–3257.

Igathinathane, C., Melin, S., Sokhansanj, S., Bi, X., Lim, C., Pordesimo, L. and Columbus, E. 2009a. Machine vision based particle size and size distribution determination of airborne dust particles of wood and bark pellets. Powder Technol. 196, 202–212.

Igathinathane, C., Pordesimo, L. and Batchelor, W. 2009b. Major orthogonal dimensions measurement of food grains by machine vision using imagej. Food Res. Int. 42, 76–84.

Igathinathane, C., Pordesimo, L., Columbus, E. P., Batchelor, W. D. and Sokhansanj, S. 2009c. Sieveless particle size distribution analysis of particulate materials through computer vision. Comput. Electron. Agric. 66, 147–158.

Igathinathane, C., Ulusoy, U. and Pordesimo, L., 2012. Comparison of particle size distribution of celestite mineral by machine vision Rvolume approach and mechanical sieving. Powder Technol. 215, 137–146.

Klasek, S., Womac, A., Yoder, D. and Hayes, D. 2006. Terminal velocity determination for component separation of biomass. In: American Society of Agricultural and Biological Engineers Annual International Meeting. Portland, Oregon, USA, pp. 9–12.

Kumar Pothula, A., Igathinathane, C., Kronberg, S. and Hendrickson, J. 2014. Digital image processing based identification of nodes and internodes of chopped biomass stems. Computers and Electronics in Agriculture. 105, 54-65.

Labbe, N., Philip, X. Y., Franklin, J. A., Womac, A. R., Tyler, D. D. and Rials, T.G. 2008. Analysis of switchgrass characteristics using near infrared techniques. BioResources 3, 1329–1348.

Leemans, V. and Destain, M. F. 2004. A real-time grading method of apples based on features extracted from defects. J. Food Eng. 61, 83–89.

Liu, L., Ye, X. P., Womac, A. R. and Sokhansanj, S. 2010. Variability of biomass chemical composition and rapid analysis using FT-NIR techniques. Carbohyd. Polym. 81, 820–829.

McCarthy, C., Hancock, N. and Raine, S. 2008. On-the-go machine vision sensing of cotton plant geometric parameters: first results. In: Mechatronics and machine vision in practice. Springer-Verlag, Berlin, Germany. 305-312.

McKendry, P. 2002. Energy production from biomass (part 1): overview of biomass. Bioresource Technol. 83, 37–46.

Mebatsion, H. and Paliwal, J. 2011. A fourier analysis based algorithm to separate touching kernels in digital images. Biosyst. Eng. 108, 66–74.

Moshashai, K., Almasi, M., Minaei, S., and Borghei, A. M. 2008. Identification of sugarcane nodes using image processing and machine vision technology. International Journal of Agricultural Research, 3(5), 357-364.

Wan, Y. N. 2002. Kernel handling performance of an automatic grain quality inspection system. Trans. ASAE 45, 369–377.

Wang, W. and Paliwal, J. 2006. Separation and identification of touching kernels and dockage components in digital images. Can. Biosyst. Eng. 48, 7.

Yamamoto, K., Guo, W. and Ninomiya, S. 2016. Node Detection and Internode Length Estimation of Tomato Seedlings Based on Image Analysis and Machine Learning. Sensors. 16:(7) 1044-1060.

Yan, L., Park, C. W., Lee, S. R. and Lee, C. Y. 2011. New separation algorithm for touching grain kernels based on contour segments and ellipse fitting. J. Zhejiang Univ. SC C 12, 54–61.

Ye, X. P., Liu, L., Hayes, D., Womac, A., Hong, K. and Sokhansanj, S. 2008. Fast classification and compositional analysis of cornstover fractions using fourier transform near-infrared techniques. Bioresource Technol. 99, 7323–7332.

Yore, M. W., Jenkins, B. M. and Summers, M. D. 2002. Cutting properties of rice straw. In: ASAE Annual International Meeting, Paper.

Zhang, G., Jayas, D. S. and White, N. D. 2005. Separation of touching grain kernels in an image by ellipse fitting algorithm. Biosyst. Eng. 92, 135–142.

Zhong, Q., Zhou, P., Yao, Q. and Mao, K. 2009. A novel segmentation algorithm for clustered slender-particles. Comput. Electron. Agric. 69, 118–127.