Photo background similarity clustering method based on convolutional neural network and computer

A convolutional neural network and clustering method technology, applied in the field of graphics processing, can solve problems such as high similarity, inability to guarantee the accuracy of results, and inability to calculate similarity, so as to achieve the effect of improving accuracy

Active Publication Date: 2019-12-13
上海汇付支付有限公司
View PDF5 Cites 8 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] However, when using a single pHash algorithm to calculate the similarity of pictures, it often happens that the calculated similarity between pictures with completely different contents is very high, which is very likel

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Photo background similarity clustering method based on convolutional neural network and computer
  • Photo background similarity clustering method based on convolutional neural network and computer
  • Photo background similarity clustering method based on convolutional neural network and computer

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0059] Such as figure 1 Shown, a kind of photo background similarity clustering method based on convolutional neural network, in this embodiment, mainly aiming at real commercial scene-holding ID card photo background review, utilize MTCNN (JointFace Detection and Alignment using MTCNN) based on deep neural network Multi-task Cascaded ConvolutionalNetworks, using multi-task cascaded convolutional neural network face detection and alignment) The face detection and alignment model corrects the direction of the hand-held ID card photo uploaded by the user to obtain a positive hand-held ID card photo, through migration Learn and train the instance segmentation model to segment the instance of the foreground image and extract the background image, use the deep neural network pre-trained on the scene recognition dataset to extract the features of the background image, and then use the Euclidean distance to compare in the high-dimensional space, so as to realize Cluster massive sampl...

Embodiment 2

[0096] On the other hand, the present invention also provides a computer for realizing similarity clustering of photo backgrounds based on convolutional neural network, including a processor and a memory, the memory stores a program, and when the program is executed by the processor, the following steps can be realized :

[0097] Obtain the original image and preprocess the original image based on the convolutional neural network algorithm to correct the direction of the recognition target in the original image;

[0098] Carrying out instance segmentation of the foreground image features and background image features containing the recognition target in the original image, and performing background extraction;

[0099] Background separation of the image for instance segmentation;

[0100] Perform feature extraction on the separated background image to obtain a high-dimensional spatial feature map;

[0101] Perform similarity clustering on high-dimensional spatial feature map...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a photo background similarity clustering method based on a convolutional neural network. The method comprises the following steps of preprocessing an original image based on aconvolutional neural network algorithm so as to correct a direction of an identification target in the original image; carrying out instance segmentation on foreground image features and background image features of the recognition target contained in the original image, and carrying out background extraction; performing background separation on the image subjected to instance segmentation; performing feature extraction on the separated background image to obtain a high-dimensional spatial feature map; and performing similarity clustering processing on the high-dimensional spatial feature map.The invention further provides a computer program system for implementing the method. According to the method, based on a pixel-level instance segmentation algorithm, foreground areas (portraits andidentity cards) in a real application scene are detected and removed, similarity comparison is carried out through background areas, and meanwhile, the recognition accuracy can be greatly improved byutilizing the convolutional neural network obtained through migration training.

Description

technical field [0001] The invention belongs to the technical field of image processing, and specifically relates to a convolutional neural network-based similarity clustering method for photo backgrounds and a computer. Background technique [0002] As a financial exchange between consumers and sellers, payment involves money-related links. As a third-party payment company, the first thing to do is to ensure the security of user accounts and payments. According to a multi-segment market research report, the total annual global fraud loss is about 500 million One hundred million U.S. dollars. Global losses on credit, debit, prepaid and private label payment cards totaled $16.31 billion last year alone. E-retailers and wholesalers lose more than 7.5 percent of their annual revenue to fraud, and insurance fraud (excluding health insurance) totals more than $40 billion annually. Research by DataVisor shows that large-scale financial risks have the phenomenon of "group siege"....

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06K9/62G06K9/34G06K9/32G06K9/00
CPCG06V40/16G06V40/161G06V10/243G06V10/267G06F18/231
Inventor 周晔穆海洁张锦涛
Owner 上海汇付支付有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap