An image retrieval method and device
An image retrieval and image technology, applied in the field of computer vision, can solve the problem of inaccurate retrieval results, achieve the effect of strong ease of use and practicability, low hardware requirements, and lower product costs
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Embodiment 1
[0030] figure 1 The implementation flow of the image retrieval method provided by the first embodiment is shown, and the process of the method is described in detail as follows:
[0031] In step S101, the feature points of each image in the image set are extracted to form a feature point library.
[0032] In this embodiment, in order to obtain more feature points and improve the accuracy of image retrieval, the feature points are preferably scale-invariant feature transform (Scale-invariant feature transform, SIFT) feature points.
[0033] Wherein, the feature points of each image in the extracted image set specifically include:
[0034] For each image in the image set, map all its SIFT feature points to N classes according to the minimum distance principle to obtain an N-dimensional feature vector V1, divide each value in V1 by the total number of feature points in the image to obtain a frequency feature vector V2 and V2 are the SIFT feature points of the image.
[0035] I...
Embodiment 2
[0050] Figure 6 The composition structure of the image retrieval device provided by the second embodiment of the present invention is shown, and for the convenience of description, only the parts related to the embodiment of the present invention are shown.
[0051] The image retrieval device can be applied to various terminal devices, such as pocket computers (Pocket PersonalComputer, PPC), palmtop computers, computers, notebook computers, personal digital assistants (Personal Digital Assistant, PDA), etc., and can be software running in these terminals A unit, a hardware unit, or a combination of software and hardware can also be integrated into these terminals as an independent pendant or run in the application systems of these terminals.
[0052] The image retrieval device includes a feature point extraction unit 61 , a clustering unit 62 , a class prediction unit 63 , a counting unit 64 , a score calculation unit 65 and a result output unit 66 . Among them, the specific...
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