Retinal Image Analysis: Image Processing and Feature Extraction Oriented to the Clinical Task

Retinal Image Analysis Oriented to the Clinical Task

Ophthalmology can profit greatly from the analysis of digital images because they can aid in establishing an early diagnosis even before the first symptoms appear. This dissertation [1] contributes to the digital analysis of such images and the problems that arise along the imaging pipeline of fundus photography, a field that is commonly referred to as retinal image analysis. We have dealt with...

Retinal image analysis: preprocessing and feature extraction

Image processing, analysis and computer vision techniques are found today in all fields of medical science. These techniques are especially relevant to modern ophthalmology, a field heavily dependent on visual data. Retinal images are widely used for diagnostic purposes by ophthalmologists. However, these images often need visual enhancement prior to apply a digital analysis for pathological ri...

Autonomy Oriented Computing Applied to Image Processing and Feature Extraction

This paper presents an overview of Autonomy Oriented Computing (AOC) and related approaches to image processing and feature extraction problems. The basic elements of such AOC systems are autonomous entities placed in an environment. The environment, in our case, is viewed as a twolayer 2D lattice containing an image in the 1 layer and a notice board at the 2 layer. The environment serves as th...

Feature Extraction and Image Processing

Feature Extraction to Polar Image

Some algorithms of feature extraction in existing literature studied for image processing was the gray image with one-dimensional parameter. However, some feature points’ extraction for three-dimensional color of polar image, such as the color edge extraction, inflection points, and so on, was urgently to be solved a polar color problem. For achieving quickly and accurately the color feature ex...