Abstract
The clothing image recognition technology can extract its element features from the clothing plan or physical map, and obtain clothing information, such as clothing color, outline, material, clothing designers can use this information to design new clothing. The clothing image recognition system designed based on convolutional neural network in this paper can identify various types of clothing by integrating image data information through the system. This paper compares the recognition accuracy and time-consuming of the system for different clothing, and finds that the recognition accuracy of sweaters is the lowest and the time-consuming is the longest. The recognition accuracy and number of network layers show that CNN and AlexNet have the highest recognition accuracy.
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