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Dynamic downsampling image segmentation method

A sampling image, dynamic technology, applied in image analysis, image enhancement, image data processing and other directions, can solve the problems of time-consuming segmentation process, unsatisfactory segmentation effect, target area breakage, etc., to overcome time-consuming and target breakage, image The effect of reducing the size and increasing the dividing speed

Active Publication Date: 2019-08-02
SHENZHEN GRADUATE SCHOOL TSINGHUA UNIV
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  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention is to solve the problem that the segmentation process in the prior art is very time-consuming, and for images with strong noise and low contrast, the target area is broken, and the segmentation effect is not ideal, and a dynamic down-sampling image segmentation method is proposed

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Embodiment Construction

[0028] In order to make the technical problems, technical solutions and beneficial effects to be solved by the embodiments of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0029] It should be noted that when an element is referred to as being “fixed” or “disposed on” another element, it may be directly on the other element or be indirectly on the other element. When an element is referred to as being "connected to" another element, it can be directly connected to the other element or indirectly connected to the other element. In addition, the connection can be used for both fixing function and circuit communication function.

[0030] It is to be understood that the terms "length", "width", "top", "bottom", "front"...

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Abstract

The invention provides a dynamic downsampling image segmentation method, which is a rapid and complete segmentation method for a low-contrast image in a strong noise environment, and is based on a dynamic downsampling idea, and mainly comprises the following steps of: defining a local two-dimensional entropy; carrying out dynamic downsampling on the image to obtain an optimal downsampling factor;down-sampling the original image by using the optimal down-sampling factor; carrying out binary segmentation on the image subjected to the optimal downsampling; and mapping the segmented coordinates of the target area back to the original image to realize final target segmentation. The core idea of the method is a dynamic down-sampling process, and the local two-dimensional entropy of each down-sampling result is calculated by gradually decreasing delta s by taking the size of an original image as a reference. In the process, the segmentation effect corresponding to the local two-dimensional entropy peak point not only overcomes the influence of unintentional interference factors in the image on image segmentation, but also retains the key detail information of the image, namely, the bestdownsampling factor found by people.

Description

technical field [0001] The invention relates to a dynamic down-sampling image segmentation method, which is a low-contrast image segmentation method in a strong noise environment, especially the rapid and complete segmentation of in-situ plankton images under unsatisfactory imaging conditions. Background technique [0002] Regions of Interest (ROIs) are image regions marked with rectangular frames, ellipses, or other irregular polygons after selecting image pixels based on certain calculation rules in computer vision and image processing tasks. . The extracted ROIs often contain the target to be analyzed. This method of only selecting the target area in the image can reduce the impact of other irrelevant background components on the further analysis of the target in subsequent steps, such as feature extraction and target recognition. and tracking applications. Traditional ROI extraction methods are directly based on the original Figure II Value segmentation is implemented...

Claims

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Application Information

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IPC IPC(8): G06T7/10
CPCG06T2207/20024G06T2207/20104G06T7/10
Inventor 程雪岷程凯常毕洪生蔡中华
Owner SHENZHEN GRADUATE SCHOOL TSINGHUA UNIV
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