Object Recognition based on a Simplified PCNN
- Object Recognition based on a Simplified PCNN
- 율리첸; 이다마; 김동환; 박성기
- computer vision; object recognition; 2D neural network; Region-
based Matching; Simplified Pulse Coupled Neural Network (SPCNN); Image Segmentation
- Issue Date
- International Conference on informatics in control, automation and robotics
- , 223-229
- The aim of the paper is to propose a region-based object recognition method to identify objects from complex real-world scenes. The proposed method firstly performs a colour image segmentation by a
simplified pulse coupled neural network (SPCNN) model, and the parameters of the SPCNN are
automatically set by our previously proposed parameter setting method. Subsequently, the proposed method performs a region-based matching between a model object image and a test image. A large number of object
recognition experiments have proved that the proposed method is robust against the variations in translation,
rotation, scale and illumination, even under partial occlusion and highly clutter backgrounds. Also it shows
a good performance in identifying less-textured objects, which significantly outperforms most feature-based methods.
- Appears in Collections:
- KIST Publication > Conference Paper
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