Atanaska Bosakova-Ardenska
ABSTRACT
An algorithm for automatic image thresholding with application in bread porosity evaluation is presented in this paper. The algorithm is named HisAnalysis and it is implemented on C#. It is made an assessment of accuracy between physicochemical method for bread porosity evaluation and two methods for automatic determination of porosity using Tsai algorithm for binarization and HisAnalysis algorithm. Two different types of ROI (Region of Interest) - rectangular and elliptical are used with these algorithms and the results are compared to each other. The experimental results show that the proposed algorithm with elliptical ROI has strong correlation coefficient with physicochemical method for bread porosity evaluation.
- Abutaleb A., "Automatic Thresholding of Gray-Level Pictures Using Two-Dimensional Entropy", Computer Vision, Graphics and Image Processing, 1989, vol. 47, Issue 1, pp 22--32. Google Scholar
Digital Library
- Andreeva H., L. Kostadinova-Georgieva, A. Bosakova-Ardenska, "Evaluation of porosity of bread by image processing", Food science, technology and technology (in Bulgarian), 2013, Scientific works of University of food technologies, Volume LX, ISSN 1314--7102, pp 1136--1139.Google Scholar
- Andreeva H., A. Bosakova-Ardenska, L. Kostadinova-Georgieva, "Comparison of two methods for automatic image binarization", Scientific conference "Computer science and technologies", Varna, 2014, ISSN 1312--3335, pp 138--143.Google Scholar
- Approved Standard "BULGARIA" - №02/2011 - Bread "White", Ministry of Agriculture and Food, Sofia, 2011 (in Bulgarian).Google Scholar
- Approved Standard "BULGARIA" - №04/2011 - Bread "Brown", Ministry of Agriculture and Food, Sofia, 2011 (in Bulgarian).Google Scholar
- Approved Standard "BULGARIA" - №03/2011 - Bread "Dobrudja", Ministry of Agriculture and Food, Sofia, 2011 (in Bulgarian).Google Scholar
- Bosakova-Ardenska A., "Application of global thresholding in bread porosity evaluation", International Journal of Intelligent Systems and Applications in Engineering, 2013, ISSN 2147--67992, pp 60--67.Google Scholar
- Danev A. M., H. Andreeva, A. Bosakova-Ardenska, L. Kostadinova-Georgieva, "Region of interest definition by image processing in brown bread porosity evaluation", HVP vol. 9--2017, ISSN 1311--0179, pp 26--30 (in Bulgarian).Google Scholar
- Danev A. M., H. Andreeva, A. Bosakova-Ardenska, L. Kostadinova-Georgieva, "Region of interest improvement by image processing in brown bread porosity evaluation", Union of scientists in Bulgaria, Plovdiv, 2016.Google Scholar
- Eglite A., D. Kunkulberga, "Bread choice and consumption trends", FoodBalt-2017, 2017.Google Scholar
- Gogova T., M. Baeva, "Aliments et boissons speciales (fonctionnels) a la base des cereals", Universite des technologie alimentaires, Plovdiv 2012.Google Scholar
- S.Nakov, V.Kolev, Introduction to programing with C# (in Bulgarian), Veliko Turnovo, 2011, ISBN: 978-954-400-527-6, pp. 23--25.Google Scholar
- Stauffer C., W.E.L. Grimson, "Adaptive background mixture models for real-time tracking", Computer Vision and Pattern Recognition, 1999.Google ScholarCross Ref
- Tsai, W-H, "Moment-Preserving Thresholding: A New Approach", in CVGIP, vol.29, pp 377--393, 1985.Google Scholar
- González T., A. S., A. G. Loyo-González, M. R. Munguía-Mazariegos, "Evaluation of bread made from composite wheat-sweet potato flours", International Food Research Journal vol. 21(4), 2014, ISSN (Online): 2231--7546, pp. 1683--1688Google Scholar
- Codina G.G., D. Atudorei, A. Cimpoi, S. Mironeasa, E. Todosi-Sanduleac, "Quality evaluation of wheat-pumpkin-golden flaxseed composite bread", Journal of Faculty of Food Engineering, Romania, vol. XIV (2) 2017, ISSN (Online): 2559--638, pp. 61--70.Google Scholar
- Mironeasa S., G. G. Codină, M. A. Oroian, "Bread Quality Characteristics as Influenced by the Addition of Tomato Seed Flour", Bulletin UASVM Food Science and Technology vol. 73 (2) 2016, ISSN-L 2344--2344; Print ISSN 2344--2344; Electronic ISSN 2344--5300, pp. 77--84.Google Scholar
- Hedkvist S., "Bread volume and Alkylresorcinol content in rye bread baked with high and low levels of Alkylresorcinol", Swedish University of Agricultural Sciences, Department of Food Science, Uppsala 2009.Google Scholar
- Tamba-Berehoiu R.M., C.N. Popa, V. Simion, B. S. Nedelcu, "Comparative analysis on the quality of several breads assortments available on the Romanian market and on the technological processes reliability", Scientific Papers Series Management, Economic Engineering in Agriculture and Rural Development, vol. 16 (4), 2016, PRINT ISSN 2284--7995, E-ISSN 2285--3952, pp. 361--368.Google Scholar
- Kvaal K., J. P. Wold, U.G. Indahl, P. Baardseth, T. Næs, "Multivariate feature extraction from textural images of bread", Chemometrics and Intelligent Laboratory Systems vol. 42 (1--2), 1998, pp. 141--148.Google ScholarCross Ref
- Zlatev Z. D., "Non destructive determination of the porosity of bread with computer image processing", ICTTE 2013, ISSN 1314--9474, pp. 504--509 (in Bulgarian).Google Scholar
- Torri L., Migliorini P., Masoero G., "Sensory test vs. electronic nose and/or image analysis of whole bread produced with old and modern wheat varieties adjuvanted by means of the mycorrhizal factor", Food Research International vol. 54 (2013), ISSN: 0963--9969, pp. 1400--1408.Google ScholarCross Ref
- Petrauskas A., "The application of the ultrasonic method for evaluating the porosity of bread", ULTRAGARSAS (ULTRASOUND) vol. 65, No. 3, ISSN 1392--2114, pp. 20--27.Google Scholar
- Otsu, N., (1979), "A threshold selection method from gray-level histograms", IEEE Trans. Sys., Man., Cyber. 9: 62--66.Google ScholarCross Ref
Index Terms
- Bread porosity evaluation by histogram analysis
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