A morphological analyzer for rice shape with gray and convolution processing of collected images was developed in this article based on embedded hardware platform of charge coupled device (CCD) camera and algorithm principle of convolutional neural networks (CNN). The camera gets the morphological image of rice, and translates it to gray level image, then the analyzer processes the image data using CNN network by the first and second threshold, the analyzer can get the edge of a race in the image, and gains all the pixels of the rice, counts the length and wide of the rice, gets the square of the race image. Then according the state standard, it gives the grade of the testing race. Eight groups of experimental samples were tested and analyzed, and the results showed that the absolute error of a single sample was 0.02, and the relative error was –0.31%. Meantime, the analyzer can uploaded the relative data to computer for quality control. The principle and algorithm of the rice parameter evaluation analyzer in this research is innovative and has a certain application value, which can shorten the detection time and improve the detection accuracy.