Volume 4 Number 4 (Aug. 2012)
Home > Archive > 2012 > Volume 4 Number 4 (Aug. 2012) >
IJCEE 2012 Vol.4(4): 596-599 ISSN: 1793-8163 DOI: 10.7763/IJCEE.2012.V4.565

A Simple Anomaly Detection for Spectral Imagery Using Co-occurrence Statistics Techniques

Kitti Koonsanit, Chuleerat Jaruskulchai, and Apisit Eiumnoh
Abstract—Anomaly detection has always been a hot research field of data mining. Anomaly detection is important in many fields. Automatic determination of the anomaly cluster is often needed to eliminate that anomaly cluster. In this paper, a method has been developed to determine the anomaly regions in satellite image using a data mining algorithm based on the co-occurrence matrix technique in order to determinate that anomaly. Our method consists of four stages, the first stage estimate a number of cluster by co-occurrence matrix, the second stage cluster dataset by automatic clustering algorithm, the third stage detect anomalous clusters by threshold value and the final stage defines clusters, which are lower than threshold value, to be anomalous clusters. The proposed method was tested using data from unknown number of clusters with multispectral satellite image in Thailand. The results from the tests confirm the effectiveness of the proposed method in finding the anomaly regions.

Index Terms—Anomaly detection, determination outlier cluster, co-occurrence statistics, outlier detection.

Kitti Koonsanit is with Kasetsart University, Bangkok, Thailand (e-mail: sc431137@hotmail.com).
Chuleerat Jaruskulchai is with Kasetsart University, Bangkok, Thailand. Apisit Eiumnoh is with National Center for Genetic Engineering and Biotechnology, Patumthani, Thailand.

Cite: Kitti Koonsanit, Chuleerat Jaruskulchai, and Apisit Eiumnoh, "A Simple Anomaly Detection for Spectral Imagery Using Co-occurrence Statistics Techniques," International Journal of Computer and Electrical Engineering vol. 4, no. 4, pp. 596-599, 2012.

General Information

ISSN: 1793-8163
Frequency: Semiyearly
Editor-in-Chief: Prof. Yucong Duan
Abstracting/ Indexing: EI (INSPEC, IET), Ulrich's Periodicals Directory, Google Scholar, EBSCO, Engineering & Technology Digital Library, ProQuest, and Electronic Journals Library
E-mail: ijcee@iap.org

What's New

  • Jul 27, 2017 News!

    IJCEE Vol. 9, No. 1 is available online now.   [Click]

  • Jun 29, 2017 News!

    IJCEE Vol. 7, No. 6 has been indexed by EI (Inspec) Inspec, created by the Institution of Engineering and Tech.!   [Click]

  • Jun 29, 2017 News!

    IJCEE Vol. 7, No. 5 has been indexed by EI (Inspec) Inspec, created by the Institution of Engineering and Tech.!   [Click]

  • Jun 29, 2017 News!

    IJCEE Vol. 7, No. 4 has been indexed by EI (Inspec) Inspec, created by the Institution of Engineering and Tech.!   [Click]

  • Jun 29, 2017 News!

    IJCEE Vol. 7, No. 1 has been indexed by EI (Inspec) Inspec, created by the Institution of Engineering and Tech.!   [Click]

  • Read more>>