Fusion of texture and contour based methods for object recognition
- We propose a new approach to object detection based on data fusion of texture and edge information. A self organizing Kohonen map is used as the coupling element of the different representations. Therefore, an extension of the proposed architecture incorporating other features, even features not derived from vision modules, is straight forward. It simplifies to a redefinition of the local feature vectors and a retraining of the network structure. The resulting hypotheses of object locations generated by the detection process are finally inspected by a neural network classifier based on co-occurence matrices.
Author: | Uwe Handmann, Thomas Kalinke |
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URN: | urn:nbn:de:hbz:1393-opus4-5231 |
URL: | https://ieeexplore.ieee.org/document/660589/authors#authors |
Parent Title (English): | IEEE Conference on Intelligent Transportation Systems |
Place of publication: | Boston, USA |
Document Type: | Conference Proceeding |
Language: | English |
Year of Completion: | 1997 |
Release Date: | 2019/07/09 |
Page Number: | 5 |
First Page: | 876 |
Last Page: | 881 |
Institutes: | Fachbereich 1 - Institut Informatik |
DDC class: | 000 Allgemeines, Informatik, Informationswissenschaft / 004 Informatik |
Licence (German): | ![]() |