Image retrieval method based on reinforced microstructure and context similarity
A technology of image retrieval and microstructure, applied in character and pattern recognition, instrumentation, computing, etc., can solve problems such as low retrieval accuracy, unreasonable distance measurement, and insufficient use of context information
Inactive Publication Date: 2014-09-24
STATE GRID CORP OF CHINA +3
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However, the distance measurement of the algorithm is unreasonable, and the context information is not fully utilized, so the retrieval accuracy is not high
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[0066] In order to better understand the technical scheme of the present invention, the following in conjunction with the attached figure 1 The present invention is further described. attached figure 1 A frame diagram of the image retrieval method of the present invention is described.
[0067] The steps of the image retrieval method based on enhanced microstructure and contextual similarity are as follows:
[0068] 1) The image is converted from the RGB color space to the HSV color space and quantized to obtain a color quantization map; the steps are:
[0069] For a color image g(x,y) of size M×N, it is first transformed from RGB color space to HSV color space. Then quantize the H, S, and V components into 8, 3, and 3 levels, respectively. So the color histogram has 72 bins. Denote the quantized color image as C(x,y), where c(x,y)∈{1,2,...72}.
[0070] 2) Carry out local mode quantization on the corresponding grayscale image, obtain an enhanced microstructure map based ...
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The invention discloses an image retrieval method based on a reinforced microstructure and context similarity. The image retrieval method includes the steps that images are converted into an HSV color space from an RGB color space to be quantized, so that a color quantization mapped picture is obtained; local mode quantization is conducted on a corresponding grey-scale map, a reinforced microstructure mapped picture is obtained in a mapping mode based on the quantized local mode, the mapped picture is used for filtering the color quantization mapped picture, and the filtered mapped picture is used for describing the images through the symbiotic relationship based on the color quantification values; the images in a library are sorted according to the standard distance between the images and a retrieval image, then all the images in a reference set are sorted again through a context similarity propagating method, and accordingly image retrieval is achieved. By the adoption of the image retrieval method, the local mode mapping method and the distance shortest path propagating method are introduced, a good image retrieval effect can be achieved, and the retrieval precision ratio and the recall ratio are improved to a certain degree.
Description
technical field [0001] The invention belongs to the field of computer image processing and information retrieval. It involves an image retrieval method based on enhanced microstructure and context similarity. Background technique [0002] With the development of multimedia and Internet technology, more and more image information is produced. How to efficiently retrieve them becomes a difficult problem. Image retrieval methods can be divided into three categories: text-based retrieval (TBIR), content-based retrieval (CBIR), and semantic-based retrieval (SBIR). Text-based retrieval requires a lot of manual annotation of images, which is highly subjective and expensive, and is basically not used now. Semantic-based retrieval uses machine learning methods to annotate images, but due to technical limitations, it is still immature. Therefore, the current application is more content-based image retrieval. [0003] Content-based image retrieval searches the database for the mos...
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IPC IPC(8): G06F17/30G06K9/62
CPCG06F16/5838
Inventor 王成现程伟华袁杰
Owner STATE GRID CORP OF CHINA