An image retrieval method and device, electronic equipment
An image retrieval and image technology, applied in the computer field, can solve problems such as low retrieval efficiency, and achieve the effect of improving efficiency and reducing the amount of data
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Embodiment 1
[0023] An image retrieval method disclosed in this embodiment, such as figure 1 As shown, the method includes: Step 110 to Step 130.
[0024] Step 110, based on the first image feature of the image to be retrieved, determine the binarized feature of the image to be retrieved.
[0025] First, the first image feature of the image to be retrieved is acquired.
[0026] Commonly used image features include texture features, color features, shape features, spatial relationship features, etc. Different features are suitable for different image contents and different image recognition requirements. Commonly used feature extraction methods are: Fourier transform method, Gabor transform method, wavelet transform method, neural network model extraction method, etc. During specific implementation, the specific method for obtaining the image features of the image to be retrieved may use methods in the prior art, such as extracting the image features of the image to be retrieved through a...
Embodiment 2
[0037] Such as figure 2 As shown, an image retrieval method disclosed in another embodiment of the present application includes: Step 210 to Step 240 .
[0038] Step 210, based on the first image feature of the image to be retrieved, determine the binarized feature of the image to be retrieved.
[0039] First, the first image feature of the image to be retrieved is acquired.
[0040] Preferably, the first image feature is a convolutional neural network feature. The convolutional neural network model extracts the first image feature of the image to be retrieved, that is, the convolutional neural network (CNN) feature can better express the higher-level semantic features of the image, and has been well established in the field of image classification, recognition and detection. application. In this embodiment, the implementation of the image retrieval method is specifically described by using the convolutional neural network model to extract the convolutional neural network ...
Embodiment 3
[0064] An image retrieval device disclosed in this embodiment, such as image 3 As shown, the device includes:
[0065] The binarized feature acquisition module 310 is configured to determine the binarized feature of the image to be retrieved based on the first image feature of the image to be retrieved;
[0066] An information entropy coding determination module 320, configured to determine the information entropy coding of the image to be retrieved based on the binarized features;
[0067] The image retrieval module 330 is configured to retrieve images similar to the image to be retrieved in a preset image library based on the information entropy coding; wherein, the images in the preset image library are indexed by information entropy coding.
[0068] During specific implementation, the preset image library uses the information entropy encoding of the binarized features of the image as the index encoding of the image.
[0069] optional, such as Figure 4 As shown, the imag...
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