Footprint image retrieval method based on space-time motion and feature fusion

A feature fusion and image retrieval technology, applied in the field of image processing and degree learning, can solve the problems of low accuracy and time-consuming, and achieve the effect of preserving integrity, overcoming obvious pressure, and improving retrieval efficiency and accuracy.

Active Publication Date: 2020-09-08
ANHUI UNIVERSITY
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The traditional method of image retrieval of footprints in general is to rely on the experience of experts or simple comparison algorithms. These methods not only have low accuracy
It consumes a lot of time, manpower and material resources

Method used

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  • Footprint image retrieval method based on space-time motion and feature fusion
  • Footprint image retrieval method based on space-time motion and feature fusion
  • Footprint image retrieval method based on space-time motion and feature fusion

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Embodiment Construction

[0054] In this embodiment, a footprint image retrieval method based on spatio-temporal motion and feature fusion mainly uses convolutional neural network and convolutional long-term short-term memory network to extract the spatio-temporal features in the sequence of footprints, and increases the performance of the network model. The data set used in the present invention contains more than 3,600 pieces of footprint data. After preprocessing, there are about 36,000 pieces of single footprint image data, including more than 100 people, and each person has at least 36 pieces of footprint data images, including barefoot footprints, Different kinds of sole pattern shoe prints, and three different walking speeds, each image is tagged with personnel ID information. Such as figure 1 Shown: The whole process can be divided into the following steps:

[0055] Step 1. Take a continuous footprint image of any test object at a certain walking speed, perform preprocessing operations of pse...

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Abstract

The invention discloses a footprint image retrieval method based on space-time motion and feature fusion. The footprint image retrieval method comprises the following steps: 1, preparing a bundled footprint image data set; 2, establishing a bundled footprint image preprocessing module; 3, establishing a preprocessing layer of multi-scale bundled footprint images and overall normalization; 4, weight initialization; 5, establishment of a spatial feature extraction module; 6, establishing a time sequence feature extraction module; and 7, training, testing and optimizing the network. According tothe method, the spatial feature information and the time sequence feature information of the bundled footprint images are extracted, and the specific feature fusion module is combined, so that richerspatial and temporal information of the bundled footprint images can be obtained. Differential feature information among different persons can be clustered. Therefore, the accurate value of bundled footprint image retrieval can be greatly improved.

Description

technical field [0001] The invention relates to the fields of image processing and degree learning, in particular to a retrieval method for footprint images based on spatio-temporal motion and feature fusion. Background technique [0002] Due to the influence of some factors such as bones and acquired living habits, the footprint image is not easy to camouflage. Compared with other traces such as palm prints and fingerprints, it is more unique and unique. In addition to scientific research significance, the research on footprint images can also be applied in commercial, security, criminal investigation and other fields. [0003] In recent years, the rapid rise of deep learning has made a new breakthrough in image retrieval of footprints, and the neural network has a strong learning ability. With the help of deep learning, the footprint images can not only reduce the manpower and material resources for analysis and data processing, but also greatly improve the efficiency and...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06K9/40G06N3/04G06N3/08G06F16/583
CPCG06N3/049G06N3/084G06F16/583G06V10/30G06N3/047G06N3/045G06F18/2415G06F18/253G06F18/214Y02D10/00
Inventor 唐俊鹿新王年朱明樊旭晨吴洛天李双双
Owner ANHUI UNIVERSITY
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