Detection of regions matching specified chromatic features
Computer Vision and Image Understanding
Digital Image Processing
Middle Sized Soccer Robots: ARVAND
RoboCup-99: Robot Soccer World Cup III
The Colour Image Processing Handbook (Optoelectronics, Imaging and Sensing)
The Colour Image Processing Handbook (Optoelectronics, Imaging and Sensing)
Basic Requirements for a Teamwork in Middle Size RoboCup
RoboCup 2001: Robot Soccer World Cup V
A Real-Time Image Recognition System for Tiny Autonomous Mobile Robots
Real-Time Systems
Pure reactive behavior learning using Case Based Reasoning for a vision based 4-legged robot
Robotics and Autonomous Systems
Fast object tracking through the use of artificial neural networks
AIA '08 Proceedings of the 26th IASTED International Conference on Artificial Intelligence and Applications
Neural robot detection in robocup
Biomimetic Neural Learning for Intelligent Robots
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A mobile robot should be able to analyze what it is seeing in real time rate and decide accordingly. Fast and reliable analysis of image data is one of the key points in soccer robot performance. In this paper we suggest a very fast method for object finding which uses the concept of perspective view. In our method, we introduce a set of jump points in perspective on which we search for objects. An object is estimated by a rectangle surrounding it. A vector based calculation is introduced to find the distance and angle of a robot from objects in the field. In addition we present a new color model which takes its components from different color models. The proposed method can detect all objects in each frame and their distance and angle in one scan on the jump points in that frame. This process takes about 1/50 of a second. Our vision system uses a commercially available frame grabber and is implemented only in software. It has shown a very good performance in RoboCup competitions.