NDLI: A comparative study of colour retinal image coding using vector quantization: K-Means & Fuzzy C-Means

Content Provider	IEEE Xplore Digital Library
Author	Setiawan, A.W. Suksmono, A.B. Mengko, T.L.R.
Copyright Year	2009
Description	Author affiliation: Biomedical Engineering - School of Electrical Engineering & Informatics, Institut Teknologi Bandung, Labtek VIII Lt. 3 Jl. Ganesa No. 10 Indonesia (Setiawan, A.W.; Mengko, T.L.R.) \|\| Telecommunication Engineering - School of Electrical Engineering & Informatics, Institut Teknologi Bandung, Labtek VIII Lt. 3 Jl. Ganesa No. 10 Indonesia (Suksmono, A.B.)
Abstract	Retinal colour images play an important role in supporting medical diagnosis. Digital retinal image usually are represented in such a large data volume that takes a considerable amount of time to be accessed and displayed. Digital medical image coding therefore become crucial in medical image transfer and storage in electronic medical record server. This paper is concerned to compare the vector quantization (VQ) coding using K-Means and Fuzzy C-Means algorithms. This research investigates the performance of each algorithm: objective (PSNR value) and subjective (visual). The VQ coding scheme is conducted separately to image components in each RGB channel. Reconstructed colour image is obtained by combining the VQ decoding result of each image channel. The 444 combination (coding of the R, G and B channels by the size of 4×4) produces the best subjective and objective quality of image coding. However, the optimum colour models for teleophthalmology and electronic medical record is 848 combination due to the file size, objective and subjective quality.
Starting Page	98
Ending Page	102
File Size	449275
Page Count	5
File Format	PDF
ISBN	9781424449132
DOI	10.1109/ICEEI.2009.5254807
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-08-05
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	PSNR Vector quantization K-Means Retina Decoding Medical diagnosis Image reconstruction Image coding Fuzzy C-Means Colour Retinal Image Vector Quantization Image storage Medical diagnostic imaging Biomedical imaging
Content Type	Text
Resource Type	Article

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