Three dimensional stereoscopic image recognition system based on fuzzy-neural network technology was developed. The system consists of three parts; preprocessing part, feature extraction part, and matching part. Two CCD color camera image are fed to the preprocessing part, where several operations including RGB-HSV transformation are done. A multi-layer perception is used for the line detection in the feature extraction part. Then fuzzy matching technique is introduced in the matching part. The system is realized on SUN spark station and special image input hardware system. An experimental result on bottle images is also presented
This paper investigates the use of artificial neural networks to help making a decision on matching ...
In this paper, we propose a new fuzzy structural matching scheme for space stereo vision which is ba...
[[abstract]]Fast feature matching process and high recognition rates are two important issues in fac...
The recognition of objects is one of the most challenging goals in robotic vision system. The proble...
In this paper, a new 3D reconstruction approach for 3D object recognition in neuro-vision system is ...
This paper is concerned with the application of an enhanced Fuzzy ART neural network algorithm for c...
Face recognition is the process of identifying one or more people in images or videos. It is an impo...
Object recognition and localization are often difficult by stereo images; partly because the image s...
Human face recognition (HFR) is the method of recognizing people in images or videos. There are diff...
A robust and accurate object recognition tool is presented in this paper. The paper introduced the u...
Soft computing techniques derived from artificial intelligence (AI) have been used for complex prob...
International audienceThe stereo matching is one of the most widely used algorithms in real-time ima...
Abstract:- In this paper, a 3D reconstruction approach based on wavelet analysis and neural networks...
More and more applications (path planning, collision avoidance methods) require 3D description of t...
Binocular stereo vision has the advantages of low cost and wide applicability. It is extensively use...
This paper investigates the use of artificial neural networks to help making a decision on matching ...
In this paper, we propose a new fuzzy structural matching scheme for space stereo vision which is ba...
[[abstract]]Fast feature matching process and high recognition rates are two important issues in fac...
The recognition of objects is one of the most challenging goals in robotic vision system. The proble...
In this paper, a new 3D reconstruction approach for 3D object recognition in neuro-vision system is ...
This paper is concerned with the application of an enhanced Fuzzy ART neural network algorithm for c...
Face recognition is the process of identifying one or more people in images or videos. It is an impo...
Object recognition and localization are often difficult by stereo images; partly because the image s...
Human face recognition (HFR) is the method of recognizing people in images or videos. There are diff...
A robust and accurate object recognition tool is presented in this paper. The paper introduced the u...
Soft computing techniques derived from artificial intelligence (AI) have been used for complex prob...
International audienceThe stereo matching is one of the most widely used algorithms in real-time ima...
Abstract:- In this paper, a 3D reconstruction approach based on wavelet analysis and neural networks...
More and more applications (path planning, collision avoidance methods) require 3D description of t...
Binocular stereo vision has the advantages of low cost and wide applicability. It is extensively use...
This paper investigates the use of artificial neural networks to help making a decision on matching ...
In this paper, we propose a new fuzzy structural matching scheme for space stereo vision which is ba...
[[abstract]]Fast feature matching process and high recognition rates are two important issues in fac...