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A low-complexity scale pyramid method to extract image features

An image feature, low-complexity technology, applied in character and pattern recognition, instruments, computing, etc., can solve the problem of high complexity of the scale pyramid, and achieve the effect of reducing redundant computing, reducing computing costs, and saving computing resources

Active Publication Date: 2020-09-08
PEKING UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0018] Aiming at the high complexity of the scale pyramid in the feature extraction algorithm, a new scale pyramid construction method is proposed

Method used

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  • A low-complexity scale pyramid method to extract image features
  • A low-complexity scale pyramid method to extract image features
  • A low-complexity scale pyramid method to extract image features

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Embodiment 1

[0067] This embodiment improves the scale pyramid extraction structure; scale pyramids are generated from low scales to high scales, and low-scale filtering calculations occupy the most important complexity. A new scale pyramid construction method is designed, specifically as follows figure 2 Shown:

[0068] In order to generate the high-scale image group before the low-scale image group, the fourth image of the first group is directly filtered to generate the next group of input images. The four groups of high-scale images will be directly filtered and generated, and then through the process of feature point detection, selection, sorting, etc., a list of feature points of the high-scale group will be generated. Through the locality of feature distribution, block prediction is performed on the four ungenerated images of the first group, and image blocks with low possibility of containing feature points are skipped to generate the final first group of images. Finally, the fea...

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Abstract

The method for extracting image features from a low-complexity scale pyramid according to the present invention is specifically: the original input image is filtered to generate five groups of image blocks to form a scale pyramid; the last four groups of image blocks generated by filtering are subjected to feature point detection, Obtain a list of high-scale image feature points; perform feature point detection after the first group of image blocks generated by filtering are subjected to block prediction processing; feature points detected from the first group of images are selected and described and then merged into In the high-scale image feature point list, the final feature point list of the original input image is generated. The invention can well reduce the redundant calculation in the process of generating the scale pyramid, and at the same time, the number of feature points generated by using the technology has no obvious difference compared with the original one, and the retrieval performance can be well guaranteed when the feature is used for retrieval after the feature is generated. This enables the CDVS standard to better meet the real-time requirements for extracting features in real life, save more computing resources, and reduce computing costs.

Description

technical field [0001] The invention relates to the technical field of computer image processing, in particular to a method for extracting image features from a low-complexity scale pyramid. Background technique [0002] MPEG-CDVS (Compact Descriptor for Visual Search, compact descriptor for visual search) is a standard algorithm for moving image search proposed by the International Motion Picture Experts Group MPEG. CDVS has a large number of applications in mobile search, such as WeChat, Google Goggles, etc. At the same time, the application scope of CDVS includes location retrieval, landmark recognition, product search and so on. CDVS performs image feature extraction and compression on the mobile terminal, and then streams the compressed data to the server for image retrieval. This avoids the stringent bandwidth requirements for directly transferring pictures for retrieval, and at the same time reduces the computing load and computing delay of the server. [0003] Wit...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/46
CPCG06V10/50
Inventor 贾惠柱宋嘉文李源解晓东
Owner PEKING UNIV