Image Classification Algorithm Based on Deep Neural Network and Multi-Layer Feature Learning
- DOI
- 10.2991/wartia-18.2018.53How to use a DOI?
- Keywords
- Deep Neural Network; Multi-Layer Feature Learning; Minimum Two-Order Norm; Image Classification; Image Features
- Abstract
Image classification being widely applied to computer vision is an im-age processing method to distinguish the different category targets according to the different features reflected by the image information. BOW-SVM is a relative-ly typical image classification method with higher precision, however, it’s unsatis-factory in operation performance. To improve the performance and precision more efficiently, a high-efficiency image classification method based on HOG-PCA is proposed. First of all, it is to make the feature whitening by extracting the Histogram of Oriented Gradients (HOG) features, secondly, make the random down-sampling for the scale unification, afterwards, adopt the principal component analysis (PCA) for feature mapping and finally make the nearest neighbor classification through the minimum two-order norm determination. In the experiment, the proposed method is realized and tested on the P ASCAL 2012 data set through C++ on the basis of OPENCV and Darwin to compare the precision and operation performance of this method and BOW-SVM method; according to the experiment, the proposed has higher precision and better operation performance.
- Copyright
- © 2018, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Fan Yang PY - 2018/09 DA - 2018/09 TI - Image Classification Algorithm Based on Deep Neural Network and Multi-Layer Feature Learning BT - Proceedings of the 4th Workshop on Advanced Research and Technology in Industry (WARTIA 2018) PB - Atlantis Press SP - 294 EP - 299 SN - 2352-5401 UR - https://doi.org/10.2991/wartia-18.2018.53 DO - 10.2991/wartia-18.2018.53 ID - Yang2018/09 ER -