A New Automatic Method to Adjust Parameters for Object Recognition

To recognize an object in an image, the user must apply a combination of operators, where each operator has a set of parameters. These parameters must be “well” adjusted in order to reach good results. Usually, this adjustment is made manually by the user. In this paper we propose a new method to automate the process of parameter adjustment for an object recognition task. Our method is based on reinforcement learning, we use two types of agents: User Agent that gives the necessary information and Parameter Agent that adjusts the parameters of each operator. Due to the nature of reinforcement learning the results do not depend only on the system characteristics but also the user’s favorite choices. Keywordscomponent; Parameters adjustment; image segmentation; Q-learning; reinforcement learning.