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Author:

Zhang, Wenli (Zhang, Wenli.) | Li, Honglu (Li, Honglu.) | Wang, Zhuozheng (Wang, Zhuozheng.)

Indexed by:

CPCI-S

Abstract:

Aiming at the problem of video image captured by the monitoring system under the conditions of haze, rain, snow and uneven illumination, a classification method of different illumination is proposed in this paper. Through analyzing the characteristics of different illumination images, the features of different illumination images can be extracted. The different illumination image features can be used to train and construct the classifier. Finally, the different illumination images are classified by the classifier. The experimental results show that the support vector machine (SVM) algorithm, BP neural network algorithm and k-means algorithm all can achieve the classification of different illumination images, and SVM algorithm has the highest classification accuracy and shortest running time.

Keyword:

K-means feature extraction different illumination image support vector machine BP neural network

Author Community:

  • [ 1 ] [Zhang, Wenli]Beijing Univ Technol, Pilot Coll Beijing, Beijing, Peoples R China
  • [ 2 ] [Wang, Zhuozheng]Beijing Univ Technol, Pilot Coll Beijing, Beijing, Peoples R China
  • [ 3 ] [Li, Honglu]Beijing Univ Technol, Coll Elect Informat & Control Engn, Beijing, Peoples R China

Reprint Author's Address:

  • [Zhang, Wenli]Beijing Univ Technol, Pilot Coll Beijing, Beijing, Peoples R China

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Source :

PROCEEDINGS OF THE 2017 2ND INTERNATIONAL CONFERENCE ON AUTOMATION, MECHANICAL CONTROL AND COMPUTATIONAL ENGINEERING (AMCCE 2017)

ISSN: 2352-5401

Year: 2017

Volume: 118

Page: 574-581

Language: English

Cited Count:

WoS CC Cited Count: 1

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 11

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