This paper tries to solve the above problems and proposes a food image recognition method based on neural network. However, in the field of food recognition, the degree of complexity is high, the situation is complex, and the accuracy and speed of recognition are worrying. In recent years, deep learning has also been gradually applied to food recognition. With the development of machine learning, as a branch of machine learning, deep learning has been applied in many fields such as image recognition, image segmentation, video segmentation, and so on. The depth absolute error is less than 0.2 mm, which can meet the demand of tire tread depth measurement. The experimental result indicates that the measurement method can identify the tire tread groove and determine its position and measure its depth.
An experiment was conducted on a prototype system based on the measurement method developed in this article. Finally, the depth of each groove was calculated successively. Then, the tread grooves on the profile curve were identified and their positions are determined by an algorithm developed in this research. Consequently, the center line’s pixel coordinates were transformed to world coordinates with the calibration information of the laser plane, and a profile curve of the tire radial section was obtained. Then, the image was calibrated to eliminate the lens distortion and processed to get the single-pixel center line. During the measuring, a tire tread radial section image formed by a laser plane was captured when the tire rolls over the measuring device. In order to determine the tire tread depth accurately and automatically, a tire tread depth measurement method based on machine vision was developed. The tire tread depth has strong influence on the braking performance of the vehicle and should be inspected periodically for driving safety.
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