Application of Color and Size Measurement in Food Products Inspection

Authors

  • Joko Siswantoro Universitas Surabaya, Indonesia (Scopus ID: 56192714800, Google Scholar: https://scholar.google.co.id/citations?user=aexhi0oAAAAJ&hl=id&oi=ao)

DOI:

https://doi.org/10.24002/ijis.v1i2.1923

Keywords:

color, size, food product, inspection

Abstract

Color and size are external aspects considered by consumers in purchasing a food product and are used in food product inspection using computer vision. This paper reviews recent applications of color and size measurement in food product inspection using computer vision. RGB, HSI, HSL, HSV, La*b spaces and color index are widely used to measure color in food product inspection. Color features, including value, mean, variance, and standard deviation of each channel in a color space are widely used in food product inspection. The applications of color measurement in food product inspection are for grading, detection of anomaly or damage, detection of specific content and evaluation of color changes. Length, width, thickness, average radius, Feret’s diameter, area, perimeter, volume, and surface area are common size measurements in food product inspection. The applications of size measurement in food product inspection are for estimating size, sorting, grading, detect unwanted objects or defects, and measurement of physical properties.

Author Biography

Joko Siswantoro, Universitas Surabaya, Indonesia (Scopus ID: 56192714800, Google Scholar: https://scholar.google.co.id/citations?user=aexhi0oAAAAJ&hl=id&oi=ao)

References

K. Kiliç, I. H. Boyaci, H. Köksel, and I. Küsmenoglu, “A classification system for beans using computer vision system and artificial neural networks,” J. Food Eng., vol. 78, no. 3, pp. 897–904, 2007.

L. Fernández, C. Castillero, and J. M. Aguilera, “An application of image analysis to dehydration of apple discs,” J. Food Eng., vol. 67, no. 1–2, pp. 185–193, 2005.

M. Z. Abdullah, Image Acquisition Systems. Amsterdam: Academic Press, 2008.

K. K. Patel, A. Kar, S. N. Jha, and M. A. Khan, “Machine vision system: A tool for quality inspection of food and agricultural products,” Journal of Food Science and Technology, vol. 49, no. 2. pp. 123–141, 2012.

N. Kondo, “Automation on fruit and vegetable grading system and food traceability,” Trends Food Sci. Technol., vol. 21, no. 3, pp. 145–152, 2010.

A. S. Prabuwono, R. Sulaiman, A. R. Hamdan, and A. Hasniaty, “Development of Intelligent Visual Inspection System (IVIS) for bottling machine,” in IEEE Region 10 Annual International Conference, Proceedings/TENCON, 2007, pp. 1–4.

C. Zheng, D. W. Sun, and L. Zheng, “Correlating colour to moisture content of large cooked beef joints by computer vision,” J. Food Eng., vol. 77, no. 4, pp. 858–863, 2006.

E. N. Malamas, E. G. M. Petrakis, M. Zervakis, L. Petit, and J. D. Legat, “A survey on industrial vision systems, applications and tools,” Image and Vision Computing, vol. 21, no. 2. pp. 171–188, 2003.

D. T. Pham and R. J. Alcock, Smart Inspection Systems: Techniques and Applications of Intelligent Vision. 2003.

H. Akbar and A. S. Prabuwono, “The design and development of automated visual inspection system for press part sorting,” in Proceedings of the International Conference on Computer Science and Information Technology, ICCSIT 2008, 2008, pp. 683–686.

K. León, D. Mery, F. Pedreschi, and J. León, “Color measurement in L*a*b*units from RGB digital images,” Food Res. Int., pp. 1084–1091, 2006.

J. Haiyan and Y. Jinli, “The application study of apple color grading by particle swarm optimization neural networks,” in Proceedings of the World Congress on Intelligent Control and Automation (WCICA), 2006, pp. 2651–2654.

Z. Xiaobo, Z. Jiewen, and L. Yanxiao, “Apple color grading based on organization feature parameters,” Pattern Recognit. Lett., pp. 2046–2053, 2007.

M. Mohebbi, M. R. Akbarzadeh-T, F. Shahidi, M. Moussavi, and H. B. Ghoddusi, “Computer vision systems (CVS) for moisture content estimation in dehydrated shrimp,” Comput. Electron. Agric., pp. 128–134, 2009.

K. Chen, X. Sun, C. Qin, and X. Tang, “Color grading of beef fat by using computer vision and support vector machine,” Comput. Electron. Agric., pp. 27–32, 2010.

D. J. Lee, J. K. Archibald, and G. Xiong, “Rapid color grading for fruit quality evaluation using direct color mapping,” IEEE Trans. Autom. Sci. Eng., pp. 292–302, 2011.

C. Zheng and D. W. Sun, “Object Measurement Methods,” in Computer Vision Technology for Food Quality Evaluation, 2008.

A. Ford and A. Roberts, “Colour Space Conversions,” Retrieved January, 1998.

M. Tkalčič and J. F. Tasič, “Colour spaces - Perceptual, historical and applicational background,” in IEEE Region 8 EUROCON 2003: Computer as a Tool - Proceedings, 2003, pp. 304–308.

R. C. Gonzalez and R. E. Woods, Digital Image Processing, 2nd ed. New Jersey: Prentice Hall, 2002.

W. Chen, Y. Q. Shi, and G. Xuan, “Identifying Computer Graphics using HSV Color Model and Statistical Moments of Characteristic Functions,” in Multimedia and Expo, 2007 IEEE International Conference on, 2007, pp. 1123–1126.

M. Z. Abdullah, S. A. Aziz, and A. M. Dos Mohamed, “Quality inspection of bakery products using a color-based machine vision system,” J. Food Qual., pp. 39–50, 2000.

H. M. Velioĝlu, smail H. Boyaci, and Ş. Kurultay, “Determination of visual quality of tomato paste using computerized inspection system and artificial neural networks,” Comput. Electron. Agric., pp. 147–154, 2011.

T. Chalidabhongse, P. Yimyam, and P. Sirisomboon, “2D/3D vision-based mango’s feature extraction and sorting,” in 9th International Conference on Control, Automation, Robotics and Vision, 2006, ICARCV ’06, 2006, pp. 1–6.

D.-J. Lee, X. Xu, J. D. Eifert, and P. Zhan, “Area and volume measurements of objects with irregular shapes using multiple silhouettes,” Opt. Eng., vol. 45, no. 2, p. 027202, 2006.

S. M. Goñi, E. Purlis, and V. O. Salvadori, “Three-dimensional reconstruction of irregular foodstuffs,” J. Food Eng., pp. 536–547, 2007.

A. B. Koc, “Determination of watermelon volume using ellipsoid approximation and image processing,” Postharvest Biol. Technol., pp. 366–371, 2007.

E. S. Bridge, R. K. Boughton, R. A. Aldredge, T. J. E. Harrison, R. Bowman, and S. J. Schoech, “Measuring egg size using digital photography: Testing Hoyt’s method using Florida Scrub-Jay eggs,” J. F. Ornithol., pp. 109–116, 2007.

T. Y. Wang and S. K. Nguang, “Low cost sensor for volume and surface area computation of axi-symmetric agricultural products,” J. Food Eng., pp. 870–877, 2007.

C. J. Du and D. W. Sun, “Estimating the surface area and volume of ellipsoidal ham using computer vision,” J. Food Eng., 2006.

M. Khojastehnazhand, M. Omid, and A. Tabatabaeefar, “Determination of orange volume and surface area using image processing technique,” Int. Agrophysics, pp. 237–242, 2009.

M. Soltani, M. Omid, and R. Alimardani, “Egg volume prediction using machine vision technique based on pappus theorem and artificial neural network,” J. Food Sci. Technol., 2014.

E. Castillo-Castaneda and C. Turchiuli, “Volume estimation of small particles using three-dimensional reconstruction from multiple views,” in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2008.

F. Mendoza, P. Dejmek, and J. M. Aguilera, “Colour and image texture analysis in classification of commercial potato chips,” Food Res. Int., pp. 1146–1154, 2007.

N. Jamil, A. Mohamed, and S. Abdullah, “Automated grading of palm oil Fresh Fruit Bunches (FFB) using neuro-fuzzy technique,” in SoCPaR 2009 - Soft Computing and Pattern Recognition, 2009, pp. 245–249.

S. Nashat, A. Abdullah, S. Aramvith, and M. Z. Abdullah, “Support vector machine approach to real-time inspection of biscuits on moving conveyor belt,” Comput. Electron. Agric., pp. 147–158, 2011.

Y. guang Yin and Y. Ding, “A close to real-time prediction method of total coliform bacteria in foods based on image identification technology and artificial neural network,” Food Res. Int., pp. 191–199, 2009.

O. C. Agustin and B. J. Oh, “Automatic milled rice quality analysis,” in Proceedings of the 2008 2nd International Conference on Future Generation Communication and Networking, FGCN 2008, 2008, pp. 112–115.

M. Omid, M. Khojastehnazhand, and A. Tabatabaeefar, “Estimating volume and mass of citrus fruits by image processing technique,” J. Food Eng., pp. 315–321, 2010.

Downloads

Published

2019-02-24

How to Cite

Siswantoro, J. (2019). Application of Color and Size Measurement in Food Products Inspection. Indonesian Journal of Information Systems, 1(2), 90–107. https://doi.org/10.24002/ijis.v1i2.1923