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Camouflage target image segmentation method based on omnibearing perception

A technology for disguising targets and image segmentation, which is applied in image analysis, image enhancement, image data processing, etc., can solve the problems of inability to locate camouflaged targets and accurately outline the boundaries of camouflaged targets, achieve excellent segmentation results, suppress interference, and be applicable sexually widespread effect

Pending Publication Date: 2022-05-27
DALIAN UNIV OF TECH
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Problems solved by technology

However, since these methods only make decisions based on region-level contextual features, they are usually unable to localize camouflaged objects in more cluttered scenes, and cannot accurately delineate the boundaries of camouflaged objects.

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  • Camouflage target image segmentation method based on omnibearing perception
  • Camouflage target image segmentation method based on omnibearing perception
  • Camouflage target image segmentation method based on omnibearing perception

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Embodiment Construction

[0070] The specific embodiments of the present invention will be further described below with reference to the accompanying drawings and technical solutions.

[0071] The datasets used in this example are CHAMELEON (76 images), CAMO (1250 images), COD10K (5066 images) and NC4K (4121 images), we use 1000 images in CAMO and 3040 images in COD10K One image is used as the training set, and the other images are used as the test set. During training, images of various sizes in the dataset are uniformly scaled to a resolution of 416×416, enhanced by random horizontal flipping and color dithering, and the output of image segmentation is rescaled to the original size of the input image. The parameters of the encoder network are initialized by the Conformer-B model pre-trained on ImageNet, and the remaining layers are initialized randomly. The implementation of OPNet is based on PyTorch and uses a stochastic gradient descent optimizer with a momentum value of 0.9 and a weight decay of ...

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Abstract

The invention belongs to the technical field of scene segmentation in computer vision, provides a camouflage target image segmentation method based on all-directional perception, designs a novel all-directional perception network oriented to precise camouflage target segmentation, and proposes a pyramid positioning module and a double-focusing module to couple local features and global representation, so as to realize image segmentation. Therefore, the camouflage target can be more accurately positioned, the boundary can be finely divided, and the problem of camouflage target segmentation in computer vision is solved. According to the method, a target segmentation result is disguised, and meanwhile, the method has effectiveness and practicability in different scenes.

Description

technical field [0001] The invention belongs to the technical field of scene segmentation (SceneSegmentation) in computer vision, realizes the segmentation of image content as a result, and particularly relates to a segmentation method for camouflaged targets in real environment images. Background technique [0002] Two-dimensional image segmentation refers to the technology of distinguishing the pixels belonging to different objects in the image to determine the size, shape and position of the target in the environmental image. It is a key step from image processing to image analysis and has great application value. . In recent years, methods related to scene segmentation, such as object detection, depth estimation, saliency region detection, and shadow detection, have achieved significant performance improvements. [0003] A considerable number of creatures in nature have evolved excellent camouflage skills (eg, protective coloration and imitation), which can camouflage t...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/13G06T7/73G06V10/82G06V10/764G06V10/80G06V10/44G06V10/28G06K9/62G06N3/04G06N3/08
CPCG06T7/13G06T7/73G06N3/08G06T2207/20081G06T2207/20084G06T2207/20112G06N3/048G06N3/045G06F18/241G06F18/253
Inventor 杨鑫梅海洋周运铎魏小鹏朴海音
Owner DALIAN UNIV OF TECH
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