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An image retrieval method and device based on image features
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An image retrieval and image feature technology, applied in the field of image recognition, can solve problems such as the reduction of SIFT feature resolution ability, and achieve the effect of improving resolution and good technical effect.
Active Publication Date: 2016-09-07
CHINA MOBILE COMM GRP CO LTD
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[0007] The present invention aims at the shortcomings of the prior art that the resolving power of SIFT features is reduced after the SIFT features are quantized, and provides an image retrieval method based on image features, which can enhance the discrimination ability of SIFT features and improve image retrieval performance
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[0048] The present invention is described in detail below in conjunction with accompanying drawing;
[0049] in, figure 1 is a schematic flow chart of the image retrieval method based on image features of the present invention;
[0050] Such as figure 1 As shown, the method includes the following steps:
[0051] S101: extracting SIFT feature points and MSER regions of the image, and obtaining all SIFT feature points included in the same MSER region;
[0052] Specifically, in this embodiment, include:
[0053] 1) Carry out all SIFT feature extractions on the image to be matched, and extract all SIFT feature points of the image, wherein, according to the prior art, the SIFT feature of each SIFT feature point is a 128-dimensional feature vector;
[0054] At the same time, in this step, the main direction and main scale of the SIFT feature point are also extracted, wherein these two parameters are important information of the SIFT feature point in the scale space and the surro...
Embodiment 2
[0068] The present invention will be described in further detail below in conjunction with specific examples.
[0069] in, figure 2 It is a schematic flow chart of a specific embodiment of the present invention.
[0070] Such as figure 2 Said, in this embodiment, the method specifically includes:
[0071] S201: Perform SIFT feature extraction on the query image, and extract all SIFT feature points of the image, wherein each of the SFT features of these SIFT feature points has a 128-dimensional vector, and obtain the quantized SIFT feature points. Direction and main scale, for example, for a certain SIFT feature point, record the main scale as S, and the main direction as
[0072] S202: Quantize the SIFT feature points to extract quantized SIFT features, the quantized SIFT features are some one-dimensional feature information, therefore, it can solve the problem caused by taking 128-dimensional SIFT features Computational problems, improve the speed of image retrieval. ...
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Abstract
The invention disclosed an image retrieval method based on image characteristics. The image retrieval method based on image characteristics includes step A, extracting scale-invariant feature transform (SIFT) interest points and maximally stable extremal regions (MSER) area of the image and obtaining all SIFT interest points in one MSER area, step B, extracting spatial feature parameter of each SIFT interest point in one MSER area according to a main direction and main scale of each SIFT interest point and position characteristic of the SIFT interest point in the MSER area, and step C, retrieving the image according to SIFT characteristics and spatial feature parameters of the SIFT interest points. When the images are matched, the matched SIFT interest points are limited spatially by the two parameters, resolution ratio of the SIFT interest points is increased greatly, mismatched points are kicked out, and image retrieval capacity is improved. The invention further discloses an image retrieval device based on the image characteristics.
Description
technical field [0001] The invention relates to an image retrieval method, in particular to an image feature-based image retrieval method and device, belonging to the field of image recognition. Background technique [0002] With the development of communication technology and multimedia technology, image and video data are growing and spreading at an explosive rate every day. In the face of large-scale image and video data, how to effectively analyze, classify, and retrieve has become a very difficult problem. [0003] At present, content-based image retrieval has become a popular research technology, which can be widely used in mobile phone image database retrieval management system, mobile phone video service retrieval system, video surveillance retrieval system, etc., and many Internet services. [0004] At present, the most widely used image retrieval method is to first extract SIFT features for the query image, then use the SIFT features of the query image to compare ...
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