Abstract
This paper presents the development of a real-time system for recognition of textured objects. In contrast to current approaches which mostly rely on specialized multiprocessor architectures for fast processing, we use a distributed network architecture to support parallelism and attain real-time performance. In this paper, a new approach to linage matching is proposed as the basis of object localization and positioning, which involves dynamic texture feature extraction and hierarchical image matching. A mask based stochastic method is introduced to extract feature points for matching. Our experimental results demonstrate that the combination of texture feature extraction and interesting point detection provides a better solution to the search of the best matching between two textured images. Furthermore, such an algorithm is implemented on a low cost heterogeneous PVM (Parallel Virtual Machine) network to speed up the processing without specific hardware requirements.
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© 1995 Springer-Verlag Berlin Heidelberg
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You, J., Zhu, W.P., Cohen, H.A., Pissaloux, E. (1995). Real-time textured object recognition on distributed systems. In: Chin, R.T., Ip, H.H.S., Naiman, A.C., Pong, TC. (eds) Image Analysis Applications and Computer Graphics. ICSC 1995. Lecture Notes in Computer Science, vol 1024. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60697-1_92
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DOI: https://doi.org/10.1007/3-540-60697-1_92
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