Abstract
Fruit classification under varying pose is still a complicated task due to various properties of numerous types of fruit. In this paper we propose fruit classification method with a novel descriptor as a combination of color and texture feature. Color feature is extracted from segmented fruit image using Color Layout Descriptor, while texture feature is extracted using Edge Histogram Descriptor. Support Vector Machine (SVM) with linear and RBF kernel is used as classifier with 10-fold cross validation. The experimental results demonstrated that our descriptor achieves classification accuracy of over 93.09 % for fruit subcategory and 100 % for fruit category from over 4200 images in varying pose.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Zhang, X., Yang, Y.-H., Han, Z., Wang, H., Gao, C.: Object Class Detection: A Survey. ACM Comput. Surv. 46, 10:1–10:53 (2013)
Parikh, D., Zitnick, C.L.: The role of features, algorithms and data in visual recognition. In: 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2328–2335 (2010)
Arivazhagan, S., Shebiah, R.N., Nidhyan, S.S., Ganesan, L.: Fruit recognition using color and texture features. Journal of Emerging Trends in Computing and Information Sciences 1, 90–94 (2010)
Seng, W.C., Mirisaee, S.H.: A new method for fruits recognition system. In: International Conference on Electrical Engineering and Informatics, pp. 130–134 (2009)
Kavdır, İ., Guyer, D.E.: Evaluation of different pattern recognition techniques for apple sorting. Biosystems Engineering 99, 211–219 (2008)
Rocha, A., Hauagge, D.C., Wainer, J., Goldenstein, S.: Automatic Fruit and Vegetable Classification from Images. Comput. Electron. Agric. 70, 96–104 (2010)
Coimbra, M.T., Cunha, J.P.S.: MPEG-7 Visual Descriptors — Contributions for Automated Feature Extraction in Capsule Endoscopy. IEEE Transactions on Circuits and Systems for Video Technology 16, 628–637 (2006)
Lai, K., Bo, L., Ren, X., Fox, D.: A large-scale hierarchical multi-view RGB-D object dataset. In: IEEE International Conference on Robotics and Automation (ICRA), pp. 1817–1824 (2011)
Sikora, T.: The MPEG-7 visual standard for content description-an overview. IEEE Transaction on Circuits and Systems for Video Technology 11, 696–702 (2001)
Kasutani, E., Yamada, A.: The MPEG-7 color layout descriptor: a compact image feature description for high-speed image/video segment retrieval. In: International Conference on Image Processing, vol. 1, pp. 674–677 (2001)
Jalab, H.A.: Image retrieval system based on color layout descriptor and Gabor filters. In: 2011 IEEE Conference on Open Systems, pp. 32–36(2011)
Annesley, J., Orwell, J., Renno, J.-P.: Evaluation of MPEG7 color descriptors for visual surveillance retrieval. In: 2nd Joint IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance, pp. 105–112 (2005)
Manjunath, B.S., Ohm, J.-R., Vasudevan, V.V., Yamada, A.: Color and texture descriptors. IEEE Transactions on Circuits and Systems for Video Technology 11, 703–715 (2001)
Zhang, D., Islam, M., Lu, G.: A review on automatic image annotation techniques. Pattern Recognition 45, 346–362 (2012)
Kimura, P.A.S., Cavalcanti, J.M.B., Saraiva, P.C., Torres, R.S., Gonçalves, M.A.: Evaluating Retrieval Effectiveness of Descriptors for Searching in Large Image Databases. Journal of Information and Data Management 2, 305–320 (2011)
Eidenberger, H.: How good are the visual MPEG-7 features? In: SPIE & Visual Communications and Image Processing, pp. 476–488 (2003)
Talib, A., Mahmuddin, M., Husni, H., George, L.E.: A weighted dominant color descriptor for content-based image retrieval. Journal of Visual Communication and Image Representation 24, 345–360 (2013)
Kim, S.M., Park, S.J., Won, C.S.: Image Retrieval via Query-by-Layout Using MPEG-7 Visual Descriptors. ETRI Journal 29, 246–248 (2007)
Chang, S.-F., Sikora, T., Purl, A.: Overview of the MPEG-7 standard. IEEE Transactions on Circuits and Systems for Video Technology 11, 688–695 (2001)
Jiang, L., Koch, A., Scherer, S.A., Zell, A.: Multi-class fruit classification using RGB-D data for indoor robots. In: 2013 IEEE International Conference on Robotics and Biomimetics (ROBIO), pp. 587–592 (2013)
Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, I.H.: The WEKA Data Mining Software: An Update. SIGKDD Explor. Newsl. 11, 10–18 (2009)
Chang, C.-C., Lin, C.-J.: LIBSVM: A Library for Support Vector Machines. ACM Transactions on Intelligent Systems and Technology (TIST) 2, 1–27 (2011)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Rachmawati, E., Supriana, I., Khodra, M.L. (2015). Multiclass Fruit Classification of RGB-D Images Using Color and Texture Feature. In: Intan, R., Chi, CH., Palit, H., Santoso, L. (eds) Intelligence in the Era of Big Data. ICSIIT 2015. Communications in Computer and Information Science, vol 516. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46742-8_24
Download citation
DOI: https://doi.org/10.1007/978-3-662-46742-8_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-46741-1
Online ISBN: 978-3-662-46742-8
eBook Packages: Computer ScienceComputer Science (R0)