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Image segmentation method and system based on full convolutional network, and storage medium

A fully convolutional network and image segmentation technology, applied in the field of image processing, can solve the problems of difficult implementation of image segmentation models and low accuracy of segmentation results, and achieve the effect of ensuring accuracy, reducing difficulty and reducing image loss.

Pending Publication Date: 2022-02-15
北京医百科技有限公司 +1
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Problems solved by technology

[0004] What the present invention aims to solve is the technical problem that the existing image segmentation model is difficult to implement or the accuracy of the segmentation result is low. Therefore, the present invention proposes an image segmentation method, system and storage medium based on a fully convolutional network

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  • Image segmentation method and system based on full convolutional network, and storage medium
  • Image segmentation method and system based on full convolutional network, and storage medium
  • Image segmentation method and system based on full convolutional network, and storage medium

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[0038]The technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Apparently, the described embodiments are some of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0039] In the description of the present invention, it should be noted that unless otherwise specified and limited, the terms "installation", "connection" and "connection" should be understood in a broad sense, for example, it can be a fixed connection or a detachable connection. Connected, or integrally connected; it can be directly connected, or indirectly connected through an intermediary, and it can be the internal communication of two elements. Those of ordinary skill in the art can understand the specific...

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Abstract

The invention provides an image segmentation method and system based on a full convolution network, and a storage medium. The method comprises the steps: carrying out the first full convolution processing of an input image, and enabling the first full convolution processing to sequentially carry out the compression, decompression, image segmentation and image reconstruction of the input image, obtaining a first reconstructed image after the first full convolution processing; obtaining a reconstruction error image between the first reconstruction image and the input image, and fusing the reconstruction error image and the first reconstruction image to obtain a prediction image; and performing second full convolution processing on the prediction image, the first full convolution processing including compression, decompression and image segmentation on the prediction image in sequence, and obtaining a foreground segmentation image after the second full convolution processing. According to the scheme provided by the invention, the full convolutional network model is simple to realize, and the obtained image segmentation result has relatively high precision.

Description

technical field [0001] The present invention relates to the technical field of image processing, in particular to an image segmentation method, system and storage medium based on a fully convolutional network. Background technique [0002] With the rapid development of computer vision technology, image segmentation algorithm has become a key step in the image processing process. Image segmentation is the process of separating the foreground and background of the image. An appropriate image segmentation algorithm needs to meet the requirements of accurate and fast segmentation results. Traditional image segmentation methods include region growing methods, clustering methods, segmentation methods based on map matching and segmentation methods based on anomaly detection, etc. The traditional segmentation method still needs human intervention, and has not achieved complete automatic segmentation, and its robustness is poor, and there are still large errors in the segmentation r...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/194G06N3/04G06V10/82G06V10/74G06K9/62
CPCG06T7/194G06T2207/20084G06N3/045G06F18/22
Inventor 张红田文宝范文新李一凡
Owner 北京医百科技有限公司
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