Abstract
The SURF (Speeded Up Robust Features) is one of the most commonly used artificial feature extraction algorithms and has a good robustness. SURF is widely used in image processing and machine vision. This paper introduces the implementation of SURF in a more comprehensive way, and applies it to the feature extraction of clothing images. The clothing features extracted by using SURF can be applied in clothing classification, identification, retrieval and matching in combination with machine learning method. It can also be used as input sample of deep neural network to improve classification or recognition accuracy.
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