Full Text Available
Note: Clicking the button above will open the full text document at the original institutional repository in a new window.
Development of an image matching scheme using feature- and area based matching techniques
Image matching is widely considered to be one of the most difficult tasks of a digital photogrammetric system. Traditionally image matching has been approached from either an area based or a feature based point of view. In recent years significant progress has been made in Area Based Matching (ABM)...
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Thesis |
| Language: | English |
| Published: |
Department of Mechanical Engineering
2016
|
| Subjects: | |
| Tags: |
No Tags, Be the first to tag this record!
|
| Summary: | Image matching is widely considered to be one of the most difficult tasks of a digital photogrammetric system. Traditionally image matching has been approached from either an area based or a feature based point of view. In recent years significant progress has been made in Area Based Matching (ABM) techniques such as Multiphoto Geometrically Constrained Least Squares Matching. Also in the field of Feature Based Matching (FBM) improvements have been made in extracting and matching image features, using for example the Forstner Operator followed by feature matching. Generally, area- and feature based matching techniques have been developed independently from each other. The aim of this research project was to design an automated image matching scheme that combines aspects of Feature Based Matching (FBM) and Area Based Matching (ABM). The reason for taking a hybrid approach is to encapsulate only the advantages of each matching scheme while cancelling out the disadvantages. The approach taken was to combine traditional aspects of ABM in digital photogrammetry with image analysis techniques found more commonly in the area of image processing and specifically machine vision. |
|---|