Currently, automatic image processing is one of the most important areas in the field of artificial intelligence, and it refers to the development of robotic systems that perform pattern recognition. One of the most useful tools for pattern recognition is systems based on fuzzy logic and artificial neural networks. In the system of technical vision (STZ), several methods and mechanisms are needed that solve the same problem in different ways, while providing the necessary indicators for the speed and reliability of identification. The essence of the hybrid image processing neuro fuzzy logical system approach in the STZ of mobile robotic systems (MRC) is to bring the original visual image into a form that allows solving the problem of recognizing its objects. In this paper, a neuro logic system for image preprocessing was proposed by using a fuzzy system in STZ. For image processing, fuzzy processing refers to a variety of fuzzy approaches, including perception, representation, image processing, segmentation, and fuzzy sets. In a comparison spot, the proposed neuro fuzzy logical system approach (NFLSA) reached 94.90% of Thresholding level, 97.56% of Color Representation, 96.47% of Image processing, 95.08% of Binarization and 95.47% of Filtering. In the process of pattern recognition, the process of preliminary fuzzy image processing is very important, because the quality of the input data of the neural network depends on it.

image processing, artificial intelligence, neuro fuzzy logic, mobile robotic systems