Abstract
In this paper, a novel method to recognize defect regions of apples based on Gabor wavelet transformation and SVM using machine vision is proposed. The method starts with background removal and object segmentation by threshold. Texture features are extracted from each segmented object by using Gabor wavelet transform, and these features are introduced to support vector machines (SVM) classifiers. Experimental results exhibit correctly recognized 85% of the defect regions of apples.
Young Scientists’ Foundation of Beijing Academy of Agriculture and Forestry Sciences (Project No. QN201119) and National High-Tech Research and Development Program of China (863 Program) (Project No. 2011AA100703).
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Heinemann, P.H., Varghese, Z.A., Morrow, C.T., Sommer III, H.J., Crasswelle, R.M.: Machine Vision Inspection of ’Golden Delicious’ Apples. Applied Engineering in Agriculture 11(6), 901–906 (1995)
Paulus, I., Schrevens, E.: Shape Characterization of New Apple Cultivars by Fourier Expansion of Digitized Images. J. Agric. Engng Res. 72, 113–118 (1999)
Zou, X.-B., Zhao, J.-W., Li, Y.: Mel Holmes. In-line detection of apple defects using three color cameras system. Computers and Electronics in Agriculture 70, 129–134 (2010)
Crowe, T.G., Delwiche, M.J.: Real-time defect detection in fruit part I: Design concepts and development of prototype hardware. Transactions of the ASAE 39(6), 2299–2308 (1996)
Crowe, T.G., Delwiche, M.J.: Real-time defect detection in fruit-part II: an algorithm and performance of a prototype system. Transactions of the ASAE 39(6), 2309–2317 (1996)
Zhiqing, W., Yang, T.: Building a rule-based machine-vision system for defect inspection on apple sorting and packing lines. Expert Systems with Applications 16(3), 307–313 (1999)
Wen, Z., Tao, Y.: Dual-camera nir/mir imaging for stem-end/calyx identification in apple defect sorting. Transactions of the ASAE 43(2), 449–452 (2000)
Kleynen, O., Leemans, V., Destain, M.-F.: Development of a multi-spectral vision system for the detection of defects on apples. Journal of Food Engineering 69(1), 41–49 (2005)
Lee, T.S.: Image representation using 2d gabor wavelets. Pattern Analysis and Machine Intelligence. IEEE Transactions on Pattern Analysis and Machine Intelligence 18(10), 959–971 (1996)
Burges, C.J.C.: A Tutorial on Support Vector Machines for Pattern Recognition. Data Mining and Knowledge Discovery 2(2), 121–167 (1998)
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© 2012 IFIP International Federation for Information Processing
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Huang, W., Zhang, C., Zhang, B. (2012). Identifying Apple Surface Defects Based on Gabor Features and SVM Using Machine Vision. In: Li, D., Chen, Y. (eds) Computer and Computing Technologies in Agriculture V. CCTA 2011. IFIP Advances in Information and Communication Technology, vol 370. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27275-2_39
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DOI: https://doi.org/10.1007/978-3-642-27275-2_39
Publisher Name: Springer, Berlin, Heidelberg
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