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A method and system for image semantic segmentation based on saliency prior

A semantic segmentation and superpixel segmentation technology, applied in the field of image processing and computer vision, can solve the problem of insufficient accuracy of segmentation results, and achieve the effect of solving the problem of marking, improving segmentation accuracy, clarity and high recognition.

Active Publication Date: 2022-07-29
HOHAI UNIV
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Problems solved by technology

[0004] The present invention provides an image semantic segmentation method and system based on saliency prior, which solves the problem of insufficient accuracy of existing segmentation results

Method used

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  • A method and system for image semantic segmentation based on saliency prior
  • A method and system for image semantic segmentation based on saliency prior
  • A method and system for image semantic segmentation based on saliency prior

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Embodiment Construction

[0041] The present invention will be further described below in conjunction with the accompanying drawings. The following examples are only used to illustrate the technical solutions of the present invention more clearly, and cannot be used to limit the protection scope of the present invention.

[0042] like figure 1 As shown, an image semantic segmentation method based on saliency prior includes the following steps:

[0043] Step 1: Perform superpixel segmentation on the image to be segmented to obtain a superpixel block.

[0044] The corresponding saliency map is calculated through the global feature of the image to be segmented, and the simple linear iterative clustering (SLIC) algorithm is used in the CIELAB color space to segment the image to obtain super pixels. The specific method is as follows:

[0045] Set the cluster center: first set the number of superpixels to be segmented. In the input image containing N1 pixels, segment K1 superpixels of uniform size, and ea...

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Abstract

The invention discloses an image semantic segmentation method and system based on saliency prior. The present invention calculates the saliency value based on depth tightness, the salient value based on position prior, the salient value based on color prior, and the salient value based on conditional random field. A saliency map fused with multi-scale features is generated, with high clarity and recognition, and improved segmentation accuracy.

Description

technical field [0001] The invention relates to an image semantic segmentation method and system based on saliency prior, belonging to the technical field of image processing and computer vision. Background technique [0002] Image semantic segmentation is to label image pixels according to their semantics to form different segmentation regions. Semantic segmentation is an important field in computer vision research, and its main task is to enable computers to know "what" each pixel in an image is. Semantic segmentation is the cornerstone technology of image understanding, and plays a pivotal role in street scene recognition and understanding of autonomous driving systems, UAV landing site judgment, and lesion identification and localization in medical images. [0003] Image semantic segmentation, as a basic technology in computer vision, is to segment the objects in the image according to their contours and label them semantically, making the image easier to understand and...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06V10/26G06V10/56G06V10/762G06V10/774G06V10/80G06K9/62
CPCG06V10/267G06V10/56G06F18/23G06F18/253G06F18/254G06F18/214
Inventor 李庆武丁成龙叶倩陈俊锋余志宏
Owner HOHAI UNIV
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