An automated detection system based on machine vision is proposed for the task of on-line detection of the crack defects on tongue spatula surface and the removal of inferior products. Firstly, based on the analysis of tongue spatula and its crack feature, a hardware device consisting of two groups of visual detection mechanisms is designed. The device is based on the chain-type conveyor belt as the basic transmission mechanism of the spatula. The specific assembly mode of chain-type conveyor belt and reflective photoelectric proximity switch is proposed to generate pulses and provide the timing sequence of the system. Based on multilevel caching mechanism, the system control architecture is designed for the collaborative allocation of the timing pulse triggering and the calling and enabling of each hardware component. In the aspect of crack detection algorithm, a method based on direction-space significance is adopted. Firstly, the preprocessing of OTSU algorithm, area screening and morphological operation is used to locate the spatula region. Then the crack feature points are extracted based on the direction-space significance. Furthermore, the candidate crack lines are generated based on the double threshold connection restriction. Finally, the cracks are accurately identified based on the characteristics of elongation angle, starting position and so on. The system performance is tested on the actual production site. The result shows that with the detection efficiency of 11 sticks per second, false positive rate (FPR) is as low as 4. 17% and false negatives rate (FNR) is 2. 68%, which are reduced by 6. 66% and 5. 36% respectively compared with the current manual detection method. It shows superior performance and has strong practical application value.