Quality control modeling of manufactured products based on image processing and fuzzy transformation techniques

Nowadays, with the expansion of various methods of obtaining information from different systems and digital cameras, the use of image processing has been widely used. Due to the increase in the huge amount of data in the industry and the need to control and monitor this amount of data, the use of image processing methods has been widely used in various industries. The analysis of these data at different levels, including the control of production line processes, is one of the most up-to-date methods in the quality control system of the statistical process of products. Therefore, using new approaches for data monitoring and quality control of manufactured products can be considered as a fruitful method. The aim of the current research is to provide a model to control the quality of manufactured products based on the image processing technique approach and using fuzzy transformations for image compression and image data processing. In order to validate the results of this research, MATLAB software was used and the developed model was compared with previous studies. The simulation results show that the proposed GLR control chart is effective in reducing the error and increasing the detection accuracy. So that in the first image after applying the changes in brightness, the warning showed that this represents the proper performance of the proposed control chart against the changes.