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#TJArk Notable Work in RoboCup 2016

Table of contents

1. Black and White Ball Perceptor
1.1 Usage
1.2 BallSpotProvider
1.3 BallPerceptor
2. Field Color Detector Based on GMM

## 1.Black and White Ball Perceptor ### 1.1 Usage In order to use this code, the B-Human's framework should be needed. If you want to use this code based on other code releases, you might need to make some change and manually adapt this code to your own code base. In order to implement this module, a copy of the modules and representations must be placed in their corresponding folders, *Src/Modules/Perception* and *Src/Representations/Perception* respectively. For further information, please refer to the [BHuman Coderelease](https://github.com/bhuman/BHumanCodeRelease "BHuman Coderelease"). For the sake of simplicity, we follow the same structure as the code. There are two modules in this algorithm: [BallSpotProvider](#headers2)and [BallPerceptor](#headers3). This page will make a short description of these two modules. ### 1.2.BallSpotProvider This module is responsible for finding ballspots that might be the center of a ball and transferring them to the BallPerceptor. As the ball used in RoboCup2016 has a black and white ball print on it, so we need to search all the white regions (provided by the ScanLine representation which provides image regions classified by colors. For further information, please refer to the [BHuman Coderelease](https://github.com/bhuman/BHumanCodeRelease "BHuman Coderelease").) and use some criteria to discard the points that is impossible a ball obviously. More information can be found in the [BallSpotProvider](https://github.com/TJArk-Robotics/Vision_Ball_Perceptor_2016/wiki/BallSpotProvider) page. ### 1.3.BallPerceptor BallPerceptor is in charge of finding a most possible ball among all the ballspots which are provided by BallSpotsProvider. It also calculates the radius, center and distance of the ballspots. Then it transfers them to blackboard so that other modules can use it for further computation. More information can be found in the [BallPerceptor](https://github.com/TJArk-Robotics/Vision_Ball_Perceptor_2016/wiki/BallPerceptor) page. ### 2. Field Color Detector Based on GMM The most important key point in a fully calibration vision system is to build an auto field color detector. In our current vision system, we are using Gaussian Mixture Model (GMM) to segment every frame of images. More information can be found in the [Field Color Detector](https://github.com/TJArk-Robotics/coderelease_2016/wiki/Field-Color-Detector) page.