How Well Can The Fusion of Gabor Filters And Local Binary Patterns Help In Identifying Gastric Lesions?

• Type: Article in International Conference Proceedings Book
• Date: 2016

Authors

Riaz, F (Author) Other; Hassan, A (Author) Other; Pedro Pimentel-Nunes (Author) FMUP; Libnio e Jorge Lage, DLEJ (Author) Other; Coimbra, M (Author) FCUP

Conference proceedings International

Title: 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016, Orlando, FL, USA, August 16-20, 2016

Pages: 1204-1207

Indexing

ISI Web of Knowledge - 1 Citation

Other information

Authenticus ID: P-00M-4PG

DOI: 10.1109/EMBC.2016.7590921

Abstract (EN): Gastroenterology imaging is a diagnostic procedure that incorporates various computer vision challenges for the design of assisted diagnostic systems. The most typical challenge is the design of more adequate visual descriptors that can assist the classification algorithms in getting good diagnostic results. Literature shows that most of the texture descriptors for feature extraction from gastric lesions are based on Gabor filters or local binary patterns (LBP). Although good results are obtained, these techniques have their shortcomings. In this paper, we aim to explore the use of fusion of Gabor filters and LBPs for characterizing gastric lesions. The images are first subjected to Gabor filtering using isotropic Gabor filters, followed by extracting LBPs from the filtered images. We validate the performance of the descriptor on a novel gastroenterology dataset: the Post-MAPS dataset. Our results show that the proposed feature set outperforms the other methods that have been considered in this paper.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 4