Multi-factor two-dimension grey level histogram based threshold segmentation method

A technology of grayscale histogram and threshold segmentation, which is applied in image analysis, image data processing, instruments, etc., can solve problems such as inability to fully reflect image information, poor threshold segmentation effect, and high noise, so as to ensure the reliability of the method and improve Effect, good effect of adaptability

Inactive Publication Date: 2017-11-21
DALIAN UNIV OF TECH
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Problems solved by technology

[0004] The technical problem to be solved by the present invention is to solve the grayscale image with a lot of noise and complexity, and the foreground and background are not clearly distinguished. The traditional grayscale histogram method has problems such as unable to fully reflect image information and poor threshold segmentation effect. A Threshold Segmentation Method for Two-Dimensional Gray Histogram of Factors

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  • Multi-factor two-dimension grey level histogram based threshold segmentation method
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  • Multi-factor two-dimension grey level histogram based threshold segmentation method

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[0052] The specific embodiments of the present invention will be described in detail below in conjunction with the technical solutions and accompanying drawings.

[0053] In this embodiment, the surface of the object to be measured is a 2.5m×3.0m t800 composite material plate, and a blue-violet ray laser with a wavelength of 460nm is projected onto the composite material plate.

[0054] The invention adopts a camera equipped with a wide-angle lens to shoot light strip images. The camera model is view works VC-12MC-M / C 65 camera, resolution: 4096×3072, image sensor: CMOS, frame rate: full frame, maximum 64.3fps, weight: 420g. The wide-angle lens model is EF 16-35mm f / 2.8L II USM, the parameters are as follows, lens focal length: f=16-35mm, APS focal length: 25.5-52.5, aperture: F2.8, lens size: 82×106. The shooting conditions are as follows: the picture pixel is 4096×3072, the focal length of the lens is 25mm, the object distance is 750mm, and the field of view is about 850mm×...

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Abstract

The invention provides a multi-factor two-dimension grey level histogram based threshold segmentation method belonging to the technical field of computer optical measurement. According to the invention, a multi-factor weight integrating image is created, a two-dimension grey level histogram is drawn and cross entropy is used for calculating the threshold value for segmenting the image. First, the weight integrating image based on three factors including neighborhood average gray level, gradient strength and gradient direction level. Further, a gray level image is combined and a gray level-integrated factor level two-dimension gray level histogram is drawn. Then an iteration method is adopted for solving gray level average values of foreground and background pixels. Finally, based on the minimum cross entropy, the optimal threshold value is calculated and the optimal threshold value is used for segmenting the image. The method provided by the invention solves a problem of image key information loss of a prior two-dimension gray level histogram; data accuracy and method reliability are ensured. The credibility of the threshold value and the image segmenting effect are improved. The whole threshold value segmenting algorithm is good in adaptability and high in validity.

Description

technical field [0001] The invention belongs to the technical field of computer vision measurement, and relates to a threshold segmentation method based on a multi-factor two-dimensional grayscale histogram. Background technique [0002] Threshold segmentation is one of the earliest researched and used methods in image segmentation, and it is one of the most commonly used image segmentation methods in various image analysis, image recognition and machine vision systems. The purpose of threshold segmentation is to find the segmentation threshold between the foreground and background of the image. Through the threshold, the entire image or a certain area of ​​the image can be divided into two areas, the foreground and the background. The gray level histogram of an image well reflects the gray level distribution information in an image, and is an important reference for threshold selection. [0003] The gray level histograms used in the existing threshold segmentation methods ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/11G06T7/13G06T7/136G06T7/194
CPCG06T7/11G06T7/13G06T7/136G06T7/194
Inventor 刘巍叶帆张洋张致远赵海洋兰志广马建伟贾振元
Owner DALIAN UNIV OF TECH
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