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Applying Feature Extraction for Classification Problems

journal contribution
posted on 2023-05-17, 02:06 authored by Chui, FCH, Ivan BindoffIvan Bindoff, Williams, RN, Byeong KangByeong Kang
With the wealth of image data that is now becoming increasingly accessible through the advent of the world wide web and the proliferation of cheap, high quality digital cameras it is becoming ever more desirable to be able to automatically classify images into appropriate categories such that intelligent agents and other such intelligent software might make better informed decisions regarding them without a need for excessive human intervention. However, as with most Artificial Intelligence (A.I.) methods it is seen as necessary to take small steps towards your goal. With this in mind a method is proposed here to represent localised features using disjoint sub-images taken from several datasets of retinal images for their eventual use in an incremental learning system. A tile-based localised adaptive threshold selection method was taken for vessel segmentation based on separate colour components. Arteriole-venous differentiation was made possible by using the composite of these components and high quality fundal images. Performance was evaluated on the DRIVE and STARE datasets achieving average specificity of 0.9379 and sensitivity of 0.5924.

History

Publication title

International Journal of Signal Processing, Image Processing and Pattern Recognition

Issue

No 1. March 2009

Pagination

1-16

ISSN

2005-4254

Department/School

School of Information and Communication Technology

Publisher

SERSC

Place of publication

Republic of Korea

Rights statement

© World Academy of Science, Engineering and Technology 2009.

Repository Status

  • Restricted

Socio-economic Objectives

Expanding knowledge in the information and computing sciences

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