Component recognition method based on deep learning and machine vision

Traditional component coding recognition adopts manual recognition or primitive machine vision technology in the electronic component testing and screening industry, which has the issues of low testing efficiency and high recognition error rate. Therefore, we proposed a novel method of component coding recognition based on machine vision combining with deep learning. The machine vision imaging system have been developed to obtain the images of component, and the processing operators such as grayscale conversion, mean filter, slant correction and other techniques are used for preprocessing. The component coding of different types and materials were recognized by deep learning model of deep convolution neural network. Extensive experiments in the component testing center and comparisons with traditional recognition demonstrate that this method has high recognition accuracy and wide range of components recognition.