Image retrieval method, device and system

Abstract

The invention discloses an image retrieval method comprising the following steps of: firstly, carrying out grey level transformation and noise reduction treatment on a scene image acquired by an image module to obtain a scene grey image; then, detecting a target object outline in the scene grey image; and finally, updating the target grey image or the feature description of the target grey image in the target object outline to an image retrieval server end for image retrieval. Correspondingly, the invention also discloses an image retrieval device, a mobile terminal and an image retrieval system. Before image retrieval, a target object is extracted precisely through outline detection, so that the influence of an image background to an image retrieval result is effectively reduced, and the retrieval precision is improved.

Description

technical field [0001] The invention relates to the field of image processing, in particular to an image retrieval method, device and system. Background technique [0002] There are two types of image retrieval: text-based and content-based. At present, image retrieval provided by most search engines is text-based retrieval, that is, free word retrieval is performed based on external image information or artificially marked keywords. Text-based image retrieval needs to associate images with text. Obtaining image retrieval results, the retrieval accuracy is greatly affected by keywords, and the visual features (color or texture, etc.) contained in images often cannot be objectively described in text, and differences in subjective understanding will lead to mismatches in image retrieval mistake. At the same time, the establishment of the database requires a lot of manual operations, and the cost is high. [0003] With the emergence of large-scale digital image databases, te...

AI Technical Summary

Problems solved by technology

The existing mobile image retrieval is to directly upload the scene images collected by the camera module of the mobile terminal to the retrieval server for image retrieval. This method not only has a large amount of data, but also requires high network bandwidth. When collecting the image of the target object, the background content near the target object is often collected, and the background content of the image will cause serious interference in the image retrieval process, thus seriously affecting the accuracy of image retrieval

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