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Target detection through image processing and resilient propagation algorithms
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DOI：10.1016/S0925-2312(00)00301-5.png)
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This paper deals with target detection studies using the image processing method as well as resilient propagation-based neural network paradigm. In the resilient propagation-based algorithms, the pre-processing operation to extract features of relevance is done using the moment invariance method. These features are then fed as input to the resilient propagation neural network. RPROP (resilient propagation) is an adaptive technique based on the standard backpropagation algorithm. This RPROP algorithm is also implemented in ADSP-21062 assembly language, since a digital signal processor (DSP) execution is much faster than the normal PC execution, as speed is desirable in real time. It is observed that the resilient propagation-based target detection is better compared to the image processing method of target detection. The main objectives of the paper are the demonstration of the applicability of moment invariant features to neural network-based target detection method and implementation of the technique using a DSP chip, ADSP-21062. (C) 2000 Elsevier Science B.V. All rights reserved.
Keyword:
automatic target detection
resilient propagation
back propagation
moment invariance
期刊
IF:
6.5
论文数:
2.5W
被引数:
6.5W
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