Fast classification of discrete shape contours
Pattern Recognition
Silhouette-based occluded object recognition through curvature scale space
Machine Vision and Applications
Geometric and Illumination Invariants for Object Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Using cross-ratios to model curve data for aircraft recognition
Pattern Recognition Letters
Histogram of oriented normal vectors for object recognition with a depth sensor
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part II
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We propose an object description and recognition approach based on the relationship between the arc length and tangent orientation angle of object contours in this paper. According to the approach, B-spline curves are firstly used to approximate contours to get the smooth variance of the arc length and tangent orientation angle, and then B-spline curves are divided into sets of simple patches, which compose the feature chains of contours. We also propose two description functions of contours, and discuss their invariance to translation, rotation and scaling transformations. In matching, because the features to be used are only several different patches of contours not the whole ones, our approach can be used to recognize not only objects with different scaling and poses, but also objects be partly occluded or absent. We conducted experiments with a set of airplane images and got a much high recognition rate.