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Image saliency target detection method combined with edge information

A technology of edge information and target detection, which is applied in the field of image processing, can solve the problems that the target does not have a contour, ignores the edge information of the salient target, etc., and achieves the effect of improving integrity and accuracy

Pending Publication Date: 2022-03-04
HANGZHOU DIANZI UNIV
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AI Technical Summary

Problems solved by technology

[0004] The existing image salient target segmentation methods often ignore the edge information of the salient target, resulting in the segmented target not having a complete outline

Method used

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  • Image saliency target detection method combined with edge information
  • Image saliency target detection method combined with edge information
  • Image saliency target detection method combined with edge information

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Embodiment Construction

[0015] The method of the present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0016] figure 1 It is a block diagram of a salient object detection network according to an embodiment of the present invention.

[0017] An image salient object detection method combined with edge information, the steps are as follows:

[0018] step 1):

[0019] Image features are encoded using a Resnet34 network pretrained on ImageNet. Take out the output features F of conv1, conv2_3, conv3_4, conv4_6, conv5_3 1 , F 2 , F 3 , F 4 , F 5 as the output of the 5 layers of the encoder. The known input feature is (H, W, 3) (where H, W, 3 are the height, width, and number of channels of the feature, respectively). Then the output feature of conv1 is F 1 (H,W,64), the output feature of conv2_3 is F 2 (H / 2,W / 2,64), the output feature of conv3_4 is F 3 (H / 4,W / 4,128), the output feature of conv4_6 is F 4 (H / 8,W / 8,256), the output featu...

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Abstract

The invention discloses an image saliency target detection method combined with edge information, which comprises the following steps of: firstly, performing feature extraction on an input image by using an encoder network to obtain features of five different scales; in the decoder step, an edge information module is used for processing the feature information of the first layer, the second layer and the third layer to obtain an edge prediction map; processing the features of the fourth layer and the fifth layer, and adding the features with the edge prediction map; then splicing is carried out along the channel dimension, the channel is compressed through conv processing, and a sigmoid activation function is used to finally obtain a prediction saliency map of the network; and finally, optimizing the whole model network by using a loss function. According to the method, the accuracy of image salient target detection can be effectively improved. And by using the edge information extraction module, the integrity of the salient target can be effectively improved.

Description

technical field [0001] The invention belongs to the field of image processing, and specifically designs an image salient object detection method for edge information of a salient object. Background technique [0002] Image salient object detection refers to the automatic segmentation of salient objects in images by computer. The technology has a wide range of application scenarios, such as image compression, or as a preprocessing task for object recognition, semantic segmentation, object tracking, etc. [0003] In order to obtain accurate image salient object segmentation results, the traditional solution is to manually design a feature extraction method, and then perform pixel-by-pixel classification based on this feature. [0004] The existing image salient target segmentation methods often ignore the edge information of the salient target, resulting in the segmented target not having a complete outline. Therefore, this paper proposes methods that can effectively fuse ob...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/13G06N3/04G06N3/08
CPCG06T7/13G06N3/08G06T2207/20081G06T2207/20084G06N3/048G06N3/045
Inventor 颜成钢万斌王廷宇孙垚棋张继勇李宗鹏
Owner HANGZHOU DIANZI UNIV
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