An enhanced segmentation of blood vessels in retinal images using Contourlet

S. H. Rezatofighi, A. Roodaki, H. Ahmadi Noubari

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

10 Citations (Scopus)


Retinal images acquired using a fund us camera often contain low grey, low level contrast and are of low dynamic range. This may seriously affect the automatic segmentation stage and subsequent results; hence, it is necessary to carry-out preprocessing to improve image contrast results before segmentation. Here we present a new multi-scale method for retinal image contrast enhancement using Contourlet transform. In this paper, a combination of feature extraction approach which utilizes Local Binary Pattern (LBP), morphological method and spatial image processing is proposed for segmenting the retinal blood vessels in optic fundus images. Furthermore, performance of Adaptive Neuro-Fuzzy Inference System (ANFIS) and Multilayer Perceptron (MLP) is investigated in the classification section. The performance of the proposed algorithm is tested on the publicly available DRIVE database. The results are numerically assessed for different proposed algorithms.

Original languageEnglish
Title of host publicationProceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages4
ISBN (Print)9781424418152
Publication statusPublished - 14 Oct 2008
Externally publishedYes
EventInternational Conference of the IEEE Engineering in Medicine and Biology Society 2008 - Vancouver Convention and Exhibition Centre, Vancouver, Canada
Duration: 20 Aug 200825 Aug 2008
Conference number: 30th (Proceedings)


ConferenceInternational Conference of the IEEE Engineering in Medicine and Biology Society 2008
Abbreviated titleEMBS 2008
Internet address

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