전자공학회논문지B (Journal of the Korean Institute of Telematics and Electronics B)
- 제33B권5호
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- Pages.60-72
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- 1996
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- 1016-135X(pISSN)
Hopfield 신경회로망을 이용한 모델 기반형 3차원 물체 인식
Model-based 3-D object recognition using hopfield neural network
초록
In this paper, a enw model-base three-dimensional (3-D) object recognition mehtod using hopfield network is proposed. To minimize deformation of feature values on 3-D rotation, we select 3-D shape features and 3-D relational features which have rotational invariant characteristics. Then these feature values are normalized to have scale invariant characteristics, also. The input features are matched with model features by optimization process of hopjfield network in the form of two dimensional arrayed neurons. Experimental results on object classification and object matching with the 3-D rotated, scale changed, an dpartial oculued objects show good performance of proposed method.
키워드