An Optimal Detection of Polyp and Ulcer in WCE Images using Fast BEMD with DLac Analysis”
Sharad T. Jadhav1, Sanjay H. Dabhole2

1Sharad T. Jadhav, Ph.D Scholar, Department of Electronics and Communication, AISECT Dr. C.V. Raman University, Kota Bilaspur (Chhattisgarh), India.
2Sanjay H. Dabhole, Ph.D Scholar, Department of Electronics and Communication, AISECT Dr. C.V. Raman University, Kota Bilaspur (Chhattisgarh), India.
Manuscript received on 10 December 2014 | Revised Manuscript received on 20 December 2014 | Manuscript Published on 30 December 2014 | PP: 108-114 | Volume-4 Issue-7, December 2014 | Retrieval Number: G1931124714/14©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: The main contribution of this paper is the presentation of a novel tool for WCE image analysis and classification by exploiting color-texture features. The proposed scheme has based on the ingenious combination of BEEMD and DLac, applied on the green/red component of WCE images in order to identify ulcerations. BEEMD, apart from an adaptive image denoising tool, was exploited to reveal the intrinsic components (IMFs) of the images in order to achieve data driven, Coefficient of Variance (CV), boost the distinctness between polyp and ulcer regions and facilitate DLac analysis to extract efficient texture characteristics. Optimum IMF selection based on the structure patterns of IMFs disclosed by DLac. The optimum IMFs are used to reconstruct a new refined image. The proposed approach has evaluated on selected WCE images, captured from patients, depicting ulcer and polyp tissue. The optimum image components (IMFs) that contain the majority of texture information include IMFs 5 and 8. Individual IMFs score up to 85.8% classification accuracy, while their exploitation as a group enhances the detection rate up to 94.3% for ulcer and polyp tissue.
Keywords: IMF, DLAC, CV, POLYP, Ulcer, WCE, EMD, BEEMD,GI.

Scope of the Article: Image analysis and Processing