A neural network approach to geographic image analysis

Author

Tchimev, Plamen ; Moritani, Naoya ; Georgiev, Georgi ; Valova, Iren

Author_Institution

Tokyo Inst. of Technol., Yokohama, Japan

fYear

2000

fDate

2000

Firstpage

58

Lastpage

62

Abstract

We have developed a method based on the precise pixel-to-pixel matching between two images. This is done by automatic generation of displacement vectors, carrying the information of differences between the two images. For generating a layer of vectors defining the information of displacement we use a neural network with self-learning architecture. The proposed algorithm perform successful mapping, which can be quantitatively measured as 90% correct recognition as demonstrated by the results

Keywords

geography; image matching; learning (artificial intelligence); neural nets; vectors; automatic generation; displacement vectors; geographic image analysis; image differences; image matching; mapping; neural network; precise pixel-to-pixel matching; recognition; self-learning architecture; Algorithm design and analysis; Degradation; Filtering; Image analysis; Image edge detection; Image generation; Neural networks; Performance evaluation; Pixel; Smoothing methods;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Analysis and Interpretation, 2000. Proceedings. 4th IEEE Southwest Symposium

Conference_Location

Austin, TX

Print_ISBN

0-7695-0595-3

Type

conf

DOI

10.1109/IAI.2000.839571

Filename

839571