Description of Evolutional Changes in Image Time Sequences Using MPEG-7 Visual Descriptors
Colour and texture visual descriptors have been developed to represent structural features of images, mainly under the Query-by-Example (QBE) image retrieval paradigm. This paper explores applicability of MPEG-7 visual descriptors to describe and measure evolutional changes in image time sequences, using a fruit rotting process as an example. The research found that MPEG-7 visual descriptors can be applied to describe evolutional changes in image time sequences. The experimental results are provided using bananas captured in image time sequences. The results show the desirable monotonicity of description metrics of MPEG-7 similarity matching for image time sequences and their sensitivity to practical image acquisition conditions. Our experiments demonstrate that Colour Layout descriptors (CLD) and Scalable Colour descriptor (SCD) describe the changes that are consistent to the degree of visual changes while CLD and Homogeneous Texture descriptor (HTD) are more robust to variations of image data due to practical image acquisition conditions.
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- 1.Martinez, J.: MPEG-7 Overview. ISO/IEC JTC1/SC29/WG11, N5525 (2003)Google Scholar
- 2.ISO/IEC 15938-3:2001. Multimedia Content Description Interface - Part 3: VisualGoogle Scholar
- 3.Ndjiki-Nya, J., et al.: Subjective Evaluation of the MPEG-7 Retrieval Accuracy Measure (ANMRR). ISO/IEC JTC1/SC29/WG11, M2029 (2000)Google Scholar
- 5.ISO/IEC 15938-8:2001. Multimedia Content Description Interface - Part 8: Extraction and Use of MPEG-7 DescriptionsGoogle Scholar
- 6.Manjunath, B.S., et al.: Introduction to MPEG-7. Wiley, Chichester (2002)Google Scholar
- 7.Njoroge, J.B., et al.: Automatic Fruit Grading System using Image Processing. In: Proc. of the 41st SICE Annual Conf., vol. 2 (2002)Google Scholar
- 8.Chan, W.H., et al.: Vision based fruit sorting system using measures of fuzziness and degree of matching. In: IEEE International Conference on Systems, Man, and Cybernetics, vol. 3 (1994)Google Scholar
- 9.Morimoto, T., et al.: Optimization of storage system of fruits using neural networks and genetic algorithms. In: Proceedings of 1995 IEEE International Joint Conference of the Fourth IEEE International Conference on Fuzzy Systems and The Second International Fuzzy Engineering Symposium, vol. 1, pp. 20–24 (1995)Google Scholar
- 10.Aleixos, N., et al.: Assessment of citrus fruit quality using a real-time machine vision system. In: Proceedings of 15th International Conference on Pattern Recognition, vol. 1 (2000)Google Scholar