Image feature recognition method

An identification method and image feature technology, applied in the field of image processing, can solve the problems of inability to accurately identify image setting features, high probability of misidentification, etc.

Active Publication Date: 2020-01-17
GUILIN UNIV OF ELECTRONIC TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide an image feature recognition method to solve the problem that the existing image processing method cannot accurately identify the set features in the image and has a high probability of misidentification

Method used

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Embodiment Construction

[0022] The specific implementation manner of the present invention will be described in more detail below with reference to schematic diagrams. The advantages and features of the present invention will be more apparent from the following description. It should be noted that all the drawings are in a very simplified form and use imprecise scales, and are only used to facilitate and clearly assist the purpose of illustrating the embodiments of the present invention.

[0023] Such as figure 1 As shown, the present embodiment provides a method for image feature recognition, including:

[0024] Step S1: providing an image data set, performing morphological processing on each image in the image data set, and combining the morphologically processed image with the original image;

[0025] Step S2: Use a rectangular frame to mark the position of the set feature on the combined image according to the known label;

[0026] Step S3: Randomly divide the images in the image data set into...

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Abstract

The invention provides an image feature recognition method, comprising the steps: providing an image data set, carrying out the morphological processing of each image in the image data set, and combining the image after morphological processing with an original image; marking the position of a set feature of the combined image by using a rectangular frame according to a known label; images in theimage data set are randomly divided into a training set and a verification set; marking the positions of the set feature points by using a deep residual network and performing learning training on thetraining set to obtain a neural network; and testing the image in the verification set by using the neural network until the neural network meets the control requirement. According to the image feature recognition method, the residual network is used to effectively improve the identification accuracy of the set feature position in the image, and the contour of the image is not segmented, so thatall features in the image can be effectively retained, and a good experiment result is obtained.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to an image feature recognition method. Background technique [0002] During the detection of pulmonary nodules in the lungs, in the process of diagnosing lung diseases based on images, radiologists usually perform qualitative analysis on the pulmonary nodules in the images based on their own years of diagnostic experience, and there will be different results. of radiologists get divergent diagnostic results, so that there is a lot of subjectivity in the diagnostic results. Therefore, researchers combine computer-aided technology with medical images to improve the detection rate of pulmonary nodules in images. Combining computer vision technology with X-ray images can reduce the variability in judging pulmonary nodules due to individual differences among medical staff. [0003] By using machine learning, deep learning and image processing technology to process images, the...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/46G06K9/56G06K9/62G06T5/30G06N3/04G06N3/08
CPCG06T5/30G06N3/08G06V10/44G06V10/36G06N3/044G06N3/045G06F18/214G06F18/253
Inventor 侯杏娜尚玉玲康怀强张雨璇易木兰陈寿宏马峻郭玲
Owner GUILIN UNIV OF ELECTRONIC TECH
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