Image segmentation processing method and system based on deep learning, and electronic equipment

An image segmentation and deep learning technology, applied in the field of image processing, to achieve the effect of improving segmentation accuracy, effectiveness, and segmentation accuracy

Pending Publication Date: 2020-12-18
创新工场(北京)企业管理股份有限公司
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In order to solve the technical problems existing in the existing image analysis and processing, the present invention provides an image segmentation processing method and system based on deep learning,

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
  • Image segmentation processing method and system based on deep learning, and electronic equipment
  • Image segmentation processing method and system based on deep learning, and electronic equipment
  • Image segmentation processing method and system based on deep learning, and electronic equipment

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0036] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention will be further described in detail below in conjunction with the accompanying drawings and implementation examples. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0037] see Figure 1A , the first embodiment of the present invention provides a deep learning-based image segmentation processing method S10, which includes the following steps:

[0038]Step S1: Provide an image to be processed with at least one target object, and perform sub-image segmentation on the image to be processed to obtain a sub-image containing the target object and its sub-image coordinates;

[0039] Step S2, use the subgraph containing the target object to train a subgraph fine segmentation model, repeat the training until the subgraph fine segmentation model reaches ...

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 provides an image segmentation processing method and system based on deep learning, and electronic equipment. The invention is used for carrying out sub-image segmentation of to-be-processed images, training a sub-image fine segmentation model by sub-images containing target objects, carrying out repeated training till the sub-image fine segmentation model reaches a preset segmentation index, and completing the segmentation of the to-be-processed images. The sub-images containing the target object are segmented, the sub-image masks corresponding to the sub-images can be obtained,and finally the sub-image masks are spliced based on the sub-image coordinates to obtain the segmentation result of the to-be-processed images. According to the image segmentation processing method based on deep learning, transfer learning can be realized, the network training time can be reduced and the segmentation precision can be enhanced in an iterative view focusing process from a macroscopic analysis mode to a microscopic analysis mode through a sub-image segmentation mode. The invention can be widely applied to image segmentation processing of multiple target objects with multiple scales and / or high original image resolution but small target object proportion, and is especially suitable for segmentation tasks of medical images.

Description

【Technical field】 [0001] The present invention relates to the field of image processing, in particular to an image segmentation processing method based on deep learning, its system, and electronic equipment 【Background technique】 [0002] With the continuous development of artificial intelligence, the demand for image processing is also increasing. In order to better analyze and process images, the existing method is to use feature extractors to extract corresponding image features, but due to existing The limitations of image analysis and processing technology, for images of multi-target and multi-scale target objects, or images with high resolution of original images but small proportion of target objects, the required data processing time is long and it is difficult to satisfy users with high precision. The needs of image analysis and processing. [0003] Therefore, it is urgent to provide a new technical solution that can effectively solve the above-mentioned image anal...

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): G06T7/11
CPCG06T2207/10004G06T2207/20081G06T7/11
Inventor 王立新罗杰坚张晓璐
Owner 创新工场(北京)企业管理股份有限公司
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