Feature extraction based on the Bhattacharyya distance

Euisun Choi, Chulhee Lee

Research output: Contribution to conferencePaperpeer-review

9 Citations (Scopus)


In this paper, we propose a feature extraction method based on the Bhattacharyya distance. Recently, it has been reported that an accurate estimation of classification error is possible using the Bhattacharyya distance. In the proposed method, we try to find feature vectors that minimize the estimated classification error of Gaussian ML classifier. In order to find such feature vectors, we start with arbitrary initial feature vectors and update them using two optimization techniques: sequential search and global search. Since we use the error estimation equation for updating feature vectors, the search time can be reduced significantly. We first apply the algorithm to two class problems and extend it to multiclass problems. Experimental results show that the proposed feature extraction algorithm compares favorably with conventional feature extraction algorithms.

Original languageEnglish
Number of pages3
Publication statusPublished - 2000
Event2000 Intenational Geoscience and Remote Sensing Symposium (IGARSS 2000) - Honolulu, HI, USA
Duration: 2000 Jul 242000 Jul 28


Other2000 Intenational Geoscience and Remote Sensing Symposium (IGARSS 2000)
CityHonolulu, HI, USA

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Earth and Planetary Sciences(all)


Dive into the research topics of 'Feature extraction based on the Bhattacharyya distance'. Together they form a unique fingerprint.

Cite this