Affine-transformation and 2D-projection invariant k-NN classification of handwritten characters via a new matching measure
作者：
Highlights：
• We enhance k-NN classification by affine and 2D-projection invariant matchings.
• We develop acceleration methods for those distortion-tolerant matching techniques.
• We propose a matching measure using similarity in direction and curvature of edges.
• Experiments using the MNIST database show a very low error rate of 0.30%.
• The source code used in the above-mentioned experiments is uploaded.
摘要
Highlights•We enhance k-NN classification by affine and 2D-projection invariant matchings.•We develop acceleration methods for those distortion-tolerant matching techniques.•We propose a matching measure using similarity in direction and curvature of edges.•Experiments using the MNIST database show a very low error rate of 0.30%.•The source code used in the above-mentioned experiments is uploaded.
论文关键词：Matching,Affine transformation,Two-dimensional projection transformation,k-nearest neighbors,Nearest-neighbor distance of equi-gradient direction
论文评审过程：Received 10 February 2015, Revised 28 August 2015, Accepted 4 October 2015, Available online 19 October 2015, Version of Record 24 December 2015.
论文官网地址：https://doi.org/10.1016/j.patcog.2015.10.002
