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In this paper, we propose an approach for object recognition using binary local invariant features and color information. In our approach, we use a fast detector for key point detection and binary local features descriptor for key point description. For local feature matching, the Fast library for Approximated Nearest Neighbors (FLANN) is applied to match the query image and reference image in data...
This paper represents a shape recognition method using PCA (principal component analysis) and Bayesian probability with MCC (modified chain code). MCC is a shape descriptor which is invariant in 2D shapepsilas scale, translation and rotation. Shape prior information is analyzed by PCA using shape database. We recognized shapes by Bayesian probability with shape prior information. In this paper we...
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