@inproceedings{b9fc219f1f1f4dafb876f53dd1870c7c,
title = "Image recognition based on invariant moment in the projection space",
abstract = "This paper proposes a projection-based invariant moment for image recognition. A set of features invariant to image translation and scaling are obtained in the' 1-D projection space. For getting rotational invariance, Rapid transform is employed. After obtaining the invariant feature vector, threshold analysis is used for feature data optimization, and principle component analysis (PCA) is applied for feature data length compression. Experimental results show the superiority of our method over Hu and other invariant moments.",
keywords = "Principle component analysis (PCA), Projection, Rapid transform, Threshold analysis",
author = "Li, \{Jun Hong\} and Quan Pan and Cui, \{Pei Ling\} and Zhang, \{Hong Cai\} and Cheng, \{Yong Mei\}",
year = "2004",
language = "英语",
isbn = "0780384032",
series = "Proceedings of 2004 International Conference on Machine Learning and Cybernetics",
pages = "3606--3610",
booktitle = "Proceedings of 2004 International Conference on Machine Learning and Cybernetics",
note = "Proceedings of 2004 International Conference on Machine Learning and Cybernetics ; Conference date: 26-08-2004 Through 29-08-2004",
}