Skin texture detecting method and apparatus based on Gabor features
A skin texture and eigenvalue technology, applied in the field of image processing, can solve problems such as slow running speed, large memory usage, poor detection effect, etc., and achieve the effect of reducing the spatial dimension, high detection accuracy, and high accuracy
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Embodiment 1
[0024] figure 1 The implementation flow of the Gabor feature-based skin texture detection method provided by Embodiment 1 of the present invention is shown, and the method process is described in detail as follows:
[0025] In step S101, the image to be detected is divided into a plurality of image blocks.
[0026] Exemplarily, in this embodiment, the image to be detected may be divided into image blocks with a size of 16*16.
[0027] It should be noted that since the texture feature is a feature that depends on the relationship with the surrounding pixels of the image, if the image block is too small, it will not reflect this cyclic feature, and the amount of calculation will increase greatly; if the image block is too large , an image block may contain both skin texture features and non-skin texture features, which will reduce the accuracy of skin texture feature detection. In this embodiment, after passing specific experiments, the image is preferably divided into image b...
Embodiment 2
[0093] image 3 The composition structure of the skin texture detection device based on Gabor features provided by Embodiment 2 of the present invention is shown. For the convenience of description, only the parts related to the embodiment of the present invention are shown.
[0094] The skin texture detection device based on Gabor features can be a software unit, a hardware unit, or a combination of software and hardware running in the terminal device, or it can be integrated into the terminal device or run on the terminal device as an independent pendant in the application system.
[0095] The skin texture detection device based on Gabor features specifically includes:
[0096] The first image block division unit 31 is used to divide the image to be detected into a plurality of image blocks;
[0097] The first calculation unit 32 is used to convolve each color channel of each image block with a pre-established Gabor filter bank in the spatial domain to obtain k*s*r matrice...
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