Image semantic segmentation method, electronic equipment and readable storage medium

A semantic segmentation and image technology, applied in the field of image semantic segmentation method, electronic equipment and readable storage medium, can solve problems such as classification problems that cannot well balance high-level abstraction and low-level accurate positioning problems, and achieve good segmentation results. , improve the sensitivity and ensure the effect of segmentation accuracy

Active Publication Date: 2019-11-08
CHANGSHA UNIVERSITY OF SCIENCE AND TECHNOLOGY
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Problems solved by technology

[0022] Aiming at the defect that FCN cannot well balance the high-level abstract classification problem and the low-level precise positioning problem, the present invention prov

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  • Image semantic segmentation method, electronic equipment and readable storage medium
  • Image semantic segmentation method, electronic equipment and readable storage medium
  • Image semantic segmentation method, electronic equipment and readable storage medium

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[0050] In order to make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. The described embodiments are only Some of the embodiments of the present invention should not be understood as limiting the protection scope of the present invention.

[0051] In the description of the present invention, the orientation description is involved. For example, the orientation or positional relationship indicated by up, down, front, back, left, right, etc. is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present invention. , Not restrictive. When it comes to quantity description, several means one or more, and multiple means two or more.

[0052] Such as fig...

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Abstract

The invention discloses an image semantic segmentation method, electronic equipment and a readable storage medium. Based on an FCN model based on depth feature fusion, the image semantic segmentationmethod replaces the traditional convolution operation by cavity convolution, constructs original images with different resolutions to form image pyramids, hierarchically inputs the FCN model, fuses the output characteristics of the upper layer with the output characteristics of the lower layer, and fuses output features to a bottom layer from top to bottom layer by layer for transposed convolution, and the output features of the bottom layer perform transposition convolution so as to enable the output resolution to be consistent with a bottom-layer input image, thus improving the sensitivity to target positioning, and the segmentation precision is ensured through optimization processing of a full-connection conditional random field subsequently, thereby obtaining a better segmentation effect.

Description

technical field [0001] The invention relates to the technical field of image semantic segmentation, in particular to an image semantic segmentation method, electronic equipment and a readable storage medium. Background technique [0002] Semantic segmentation is one of the important cornerstones in the field of computer vision. It not only classifies each pixel in the image, but also marks the object category to which the pixel belongs in the image, that is, it can not only segment the area, but also perform content analysis on the area. label. [0003] Semantic segmentation can generally be divided into several different tasks such as figure 1 As shown, among them, figure 1 (a): pixel-level segmentation; figure 1 (b): scene analysis; figure 1 (c): Combination of localization and classification. exist figure 1 In (a), given an image, it may be necessary to distinguish all pixels in the image belonging to people and all pixels belonging to horses, and each category of p...

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Application Information

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IPC IPC(8): G06T7/11
CPCG06T7/11G06T2207/20016G06T2207/20081G06T2207/20084
Inventor 陈沅涛陶家俊王进王磊张建明陈曦邝利丹谷科刘林武王志
Owner CHANGSHA UNIVERSITY OF SCIENCE AND TECHNOLOGY
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