The advantages and disadvantages of traditional edge detection operators are analyzed; LVQ neural network is introduced to detect image edge; the detection principle and training process of network weight of LVQ is detailed, in which the result of traditional operator detection is taken as teacher signal and the input signal is based on a set of features of 5 × 5 neighborhood, such as median feature, direction feature and Kirsch operator direction feature of gray image, the calculation formula of those features is given; based on different thresholds and teacher signal types, the edge of navel orange image is detected using LVQ neural network; the results show that edge shape of the image is independent on the type and threshold of teacher signal, and as significant advantages over traditional operator detection, edge continuity is improved and overexposure suppressed.