NDLI: Landmark-based shape recognition by a modified Hopfield neural network

Content Provider	IEEE Xplore Digital Library
Author	Ansari, N. Li, K.
Copyright Year	1991
Description	Author affiliation: Dept. of Electr. & Comput. Eng., New Jersey Inst. of Technol., Newark, NJ, USA (Ansari, N.; Li, K.)
Abstract	A new method is introduced to achieve partial shape recognition by means of a modified Hopfield neural network. Given a scene consisting of partially occluded objects, a model object in the scene is hypothesized by matching the landmarks of the model with those in the scene. A local shape measure, known as the sphericity of a triangular transformation, is used as a measure of similarity between two landmarks. The hypothesis of a model object in a scene is completed by matching the model landmarks with the scene landmarks. The landmark matching task is performed by a modified Hopfield neural network. The location of the model in the scene is estimated with a least squares fit among the matched landmarks. A heuristic measure is then computed to decide if the model is in the scene.
Starting Page	93
Ending Page	97
File Size	352083
Page Count	5
File Format	PDF
ISBN	0780302338
DOI	10.1109/ICSMC.1991.169667
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1991-10-13
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Hopfield neural networks Layout Shape measurement Service robots Humans Libraries Wire Signal processing Least squares approximation Application software
Content Type	Text
Resource Type	Article

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