A comparison of image processing algorithms for edge detection, corner detection and thinning

Siddharth Parekh

Research output: ThesisMaster's Thesis

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Abstract

Image processing plays a key role in vision systems. Its function is to extract and enhance pertinent information from raw data. In robotics, processing of real-time data is constrained by limited resources. Thus, it is important to understand and analyse image processing algorithms for accuracy, speed, and quality. The theme of this thesis is an implementation and comparative study of algorithms related to various image processing techniques like edge detection, corner detection and thinning. A re-interpretation of a standard technique, non-maxima suppression for corner detectors was attempted. In addition, a thinning filter, Hall-Guo, was modified to achieve better results. Generally, real time data is corrupted with noise. This thesis also incorporates few smoothing filters that help in noise reduction. Apart from comparing and analysing algorithms for these techniques, an attempt was made to implement correlation-based optic flow
Original languageEnglish
QualificationMasters
Publication statusUnpublished - 2004

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Edge detection
Image processing
Noise abatement
Optics
Robotics
Detectors
Processing

Cite this

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title = "A comparison of image processing algorithms for edge detection, corner detection and thinning",
abstract = "Image processing plays a key role in vision systems. Its function is to extract and enhance pertinent information from raw data. In robotics, processing of real-time data is constrained by limited resources. Thus, it is important to understand and analyse image processing algorithms for accuracy, speed, and quality. The theme of this thesis is an implementation and comparative study of algorithms related to various image processing techniques like edge detection, corner detection and thinning. A re-interpretation of a standard technique, non-maxima suppression for corner detectors was attempted. In addition, a thinning filter, Hall-Guo, was modified to achieve better results. Generally, real time data is corrupted with noise. This thesis also incorporates few smoothing filters that help in noise reduction. Apart from comparing and analysing algorithms for these techniques, an attempt was made to implement correlation-based optic flow",
keywords = "Image processing, Mathematical models, Digital image processing, Edge detection, Corner detection, Thinning filters, Smoothing filters, Optical flow",
author = "Siddharth Parekh",
year = "2004",
language = "English",

}

A comparison of image processing algorithms for edge detection, corner detection and thinning. / Parekh, Siddharth.

2004.

Research output: ThesisMaster's Thesis

TY - THES

T1 - A comparison of image processing algorithms for edge detection, corner detection and thinning

AU - Parekh, Siddharth

PY - 2004

Y1 - 2004

N2 - Image processing plays a key role in vision systems. Its function is to extract and enhance pertinent information from raw data. In robotics, processing of real-time data is constrained by limited resources. Thus, it is important to understand and analyse image processing algorithms for accuracy, speed, and quality. The theme of this thesis is an implementation and comparative study of algorithms related to various image processing techniques like edge detection, corner detection and thinning. A re-interpretation of a standard technique, non-maxima suppression for corner detectors was attempted. In addition, a thinning filter, Hall-Guo, was modified to achieve better results. Generally, real time data is corrupted with noise. This thesis also incorporates few smoothing filters that help in noise reduction. Apart from comparing and analysing algorithms for these techniques, an attempt was made to implement correlation-based optic flow

AB - Image processing plays a key role in vision systems. Its function is to extract and enhance pertinent information from raw data. In robotics, processing of real-time data is constrained by limited resources. Thus, it is important to understand and analyse image processing algorithms for accuracy, speed, and quality. The theme of this thesis is an implementation and comparative study of algorithms related to various image processing techniques like edge detection, corner detection and thinning. A re-interpretation of a standard technique, non-maxima suppression for corner detectors was attempted. In addition, a thinning filter, Hall-Guo, was modified to achieve better results. Generally, real time data is corrupted with noise. This thesis also incorporates few smoothing filters that help in noise reduction. Apart from comparing and analysing algorithms for these techniques, an attempt was made to implement correlation-based optic flow

KW - Image processing

KW - Mathematical models

KW - Digital image processing

KW - Edge detection

KW - Corner detection

KW - Thinning filters

KW - Smoothing filters

KW - Optical flow

M3 - Master's Thesis

ER -