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Chicken image segmentation method and system based on multi-scale attention network

An image segmentation and attention technology, applied in the field of computer vision, can solve the problems of dense distribution and different shapes of chickens that are not considered, and achieve the effect of accelerating network convergence, improving accuracy, and enriching the extraction of advanced semantic features.

Active Publication Date: 2021-06-29
SHANDONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] It has been observed that most chickens generally prefer to live in groups, and that the chicks have similar appearance, different sizes, clumped life, motion occlusion, etc., allowing for accurate chick segmentation It is very challenging, and the existing image segmentation methods do not consider the dense distribution of chicks, different shapes, occlusion and other issues

Method used

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  • Chicken image segmentation method and system based on multi-scale attention network
  • Chicken image segmentation method and system based on multi-scale attention network
  • Chicken image segmentation method and system based on multi-scale attention network

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Embodiment 1

[0056] Such as figure 1 As shown, this embodiment provides a chicken image segmentation method based on a multi-scale attention mechanism network, extracts multi-level features through a multi-scale encoding-decoding network, and uses a dual attention mechanism to perform global and local features on the feature map Enhancement, using the combined loss of multi-scale output to supervise the entire network, effectively improving the effect of chicken image segmentation; the specific steps are as follows:

[0057] S1: Construct an image pyramid after performing multi-scale downsampling on the acquired chick image;

[0058] S2: Construct a segmentation network based on a multi-scale dual attention mechanism. The segmentation network includes two parts: encoding and decoding. The multi-scale feature map is extracted through the encoding network, and the dual attention mechanism is used to enhance global and local features. Enhanced feature decoding predicts segmentation results f...

Embodiment 2

[0129] This embodiment provides a chick image segmentation system based on a multi-scale attention network, including:

[0130] The image down-sampling module is configured to construct an image pyramid after performing multi-scale down-sampling on the acquired chick image;

[0131]The feature extraction module is configured to construct a segmentation network based on a multi-scale attention mechanism, extract multi-scale feature maps through an encoding network in the segmentation network, perform global and local feature enhancement through a dual attention mechanism, and decode and predict the enhanced features Get the segmentation result of each layer;

[0132] The image segmentation prediction module is configured to obtain a multi-scale joint loss based on the segmentation result of each layer, optimize the multi-scale attention segmentation network based on the multi-scale joint loss, and obtain the image segmentation result with the optimized multi-scale attention seg...

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Abstract

The invention discloses a chick image segmentation method and system based on a multi-scale attention network. The method comprises the steps of performing multi-scale downsampling on an acquired chick image and then constructing an image pyramid; constructing a segmentation network based on a multi-scale attention mechanism, extracting a multi-scale feature map in the segmentation network through a coding network, carrying out global and local feature enhancement through a double attention mechanism, and carrying out decoding prediction on the enhanced features to obtain a segmentation result of each layer; and obtaining multi-scale joint loss based on the segmentation result of each layer, optimizing the multi-scale attention segmentation network based on the multi-scale joint loss, and obtaining an image segmentation result by using the optimized multi-scale attention segmentation network. The chick image segmentation effect is effectively improved.

Description

technical field [0001] The invention relates to the technical field of computer vision, in particular to a chicken image segmentation method and system based on a multi-scale attention network. Background technique [0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art. [0003] In recent years, many studies have focused on observing and analyzing animal behavior to prevent disease, improve the living environment of animals, and improve animal welfare. The rapid development of artificial intelligence and computer vision technology has accelerated the process of intelligent farming. Currently, intelligent animal farming can be done through sensor-based methods and computer vision-based methods, both of which automatically observe and analyze animal behavior. The former uses specific sensor devices to obtain animal location, data and other information; for example, some method...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/10G06N3/04
CPCG06T7/10G06T2207/20081G06T2207/20084G06N3/045
Inventor 李伟黄艳
Owner SHANDONG UNIV
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