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A two-dimensional normalized Gaussian filtering method for three-dimensional surface topography feature extraction

A topographic feature and three-dimensional surface technology, applied in the field of image processing, can solve the problem of low accuracy of topographic feature recognition and achieve the effect of improving accuracy

Active Publication Date: 2019-06-21
HARBIN INST OF TECH
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  • Claims
  • Application Information

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Problems solved by technology

[0004] The purpose of the present invention is to solve the problem that the existing extracted topography features have a wide distribution in amplitude, low-amplitude features are covered by high-amplitude features, resulting in low accuracy of topography feature recognition, and propose to use Two-dimensional normalized Gaussian filter method for feature extraction of three-dimensional surface topography

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  • A two-dimensional normalized Gaussian filtering method for three-dimensional surface topography feature extraction
  • A two-dimensional normalized Gaussian filtering method for three-dimensional surface topography feature extraction
  • A two-dimensional normalized Gaussian filtering method for three-dimensional surface topography feature extraction

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specific Embodiment approach 1

[0022] Specific implementation manner 1: The specific process of the two-dimensional normalized Gaussian filtering method for extracting three-dimensional surface topography features in this embodiment is:

[0023] Step 1. Set the input of the filter as the three-dimensional image f(u, v) and the cutting length λ c , Based on the cut length λ of the three-dimensional topographic features of the image to be extracted c , Calculate the Gaussian weight function g(x,y) of the two-dimensional Gaussian filter;

[0024] Step 2: Establish the template function bf(u, v) of the three-dimensional image shape f(u, v) to avoid the edge distortion problem of the filtering result;

[0025] Step 3: Make the Gaussian weight function g(x, y) of the two-dimensional Gaussian filter move point by point on the three-dimensional shape of the input image f(u, v), and calculate the normalized filter when moving to (u, v) As a result t(u, v), after moving all the positions, the matrix of normalized filtering ...

specific Embodiment approach 2

[0026] Specific embodiment two: this embodiment is different from specific embodiment one in that in the step one, the input of the filter is assumed to be the three-dimensional image f(u, v) and the cut length λ c , Based on the cut length λ of the three-dimensional topographic features of the image to be extracted c , Calculate the Gaussian weight function g(x, y) of the two-dimensional Gaussian filter, the specific process is:

[0027] The Gaussian weight function g(x, y) of the two-dimensional Gaussian filter is expressed as:

[0028]

[0029] Where α is the Gaussian filter constant, According to the Gaussian distribution, the range of (x, y) is The number of matrix points after the value is recorded as N x With N y ; (X, y) is the point of the Gaussian weight function.

[0030] Other steps and parameters are the same as in the first embodiment.

specific Embodiment approach 3

[0031] Specific embodiment three: This embodiment is different from specific embodiments one or two in that in the second step, the template function bf(u, v) of the three-dimensional image f(u, v) is established to avoid the edge of the filtering result The distortion problem, the specific process is:

[0032]

[0033] The boundary is (u, v) is the topographic feature point to be filtered.

[0034] Other steps and parameters are the same as those in the first or second embodiment.

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Abstract

The invention discloses a two-dimensional normalized Gaussian filtering method for three-dimensional surface topography feature extraction, and relates to a Gaussian filtering method for topography feature extraction. The invention aims to solve the problem that the existing extracted morphological characteristics have relatively wide distribution in amplitude and low-amplitude characteristics arecovered by high-amplitude characteristics, so that the recognition accuracy of the morphological characteristics is low. The method comprises the following steps of: 1, setting the input of a filteras a three-dimensional shape and a cutting length, and calculating a Gaussian weight function of the two-dimensional Gaussian filter based on the cutting length of a three-dimensional shape feature tobe extracted; 2, establishing a three-dimensional shape template function; And 3, enabling the Gaussian weight function of the two-dimensional Gaussian filter to move point by point on the input three-dimensional morphology, calculating a normalized filtering result when the Gaussian weight function moves to the point of the morphology feature to be filtered, and after the Gaussian weight function moves to a complete part of position, obtaining a matrix composed of the normalized filtering result as a filtering result. The method is applied to the field of image processing.

Description

Technical field [0001] The invention is used in the field of image processing, and specifically relates to a Gaussian filtering method used for extracting topographic features. Background technique [0002] In industrial production, the surface of processed parts contains morphological features of different scales. Through the extraction of these features, it can be used to analyze the processing problems in the production process of the parts and the friction and wear problems in the use process. For example, different mechanical failure problems such as scratch wear and pitting corrosion will produce morphological features of different forms and scales. Analysis of these morphological features can help improve the production process and increase product life. Not limited to the industrial field, in the field of criminal science, through the extraction of the three-dimensional features of the bullet marks and tool marks at the crime scene, it can help criminal investigators det...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/46
Inventor 佟明斯黄穗楚潘昀路赵学增
Owner HARBIN INST OF TECH
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