阅读说明：本技术 一种基于聚焦评价算法的结构光微纳三维形貌测量方法 (Structured light micro-nano three-dimensional morphology measurement method based on focusing evaluation algorithm ) 是由 刘磊 唐燕 谢仲业 位浩杰 赵立新 胡松 于 2019-10-14 设计创作，主要内容包括：本发明是一种基于聚焦评价算法的结构光微纳三维形貌测量方法,传统的基于聚焦评价函数的三维测量方法具有测量系统简单、无损伤等特点,但由于其本质是根据物体本身纹理信息对聚焦程度进行判断,对于表面结构光滑、纹理不足的物体难以测量。本发明提出了一种结合结构光照明和聚焦评价函数的三维形貌轮廓术,可以实现对光滑和粗糙表面共存的物体测量。在测量系统中,将DMD产生的图案投影到物体表面,纵向扫描物体获得待处理图片,对于一个像素点而言,在图像序列中表现为从模糊到清晰再到模糊的过程,其中使用聚焦评价算法定位像素点成像最清晰的图片位置,再结合曲线拟合算法提取精确聚焦位置,遍历所有像素点即可获取物体三维形貌。(The invention relates to a structured light micro-nano three-dimensional morphology measuring method based on a focusing evaluation algorithm, and the traditional three-dimensional measuring method based on a focusing evaluation function has the characteristics of simple measuring system, no damage and the like, but is difficult to measure objects with smooth surface structures and insufficient textures because the focusing degree is judged according to the texture information of the objects essentially. The invention provides a three-dimensional topography profilometry combining structured light illumination and a focusing evaluation function, which can realize the measurement of an object with a smooth surface and a rough surface. In a measuring system, a pattern generated by the DMD is projected on the surface of an object, the object is longitudinally scanned to obtain a picture to be processed, for one pixel point, the process from blurring to clearness and then blurring is shown in an image sequence, wherein the most clear picture position imaged by the pixel point is positioned by using a focusing evaluation algorithm, an accurate focusing position is extracted by combining a curve fitting algorithm, and the three-dimensional appearance of the object can be obtained by traversing all the pixel points.)

1. A structured light micro-nano three-dimensional morphology measurement method based on a focusing evaluation algorithm is characterized by comprising the following steps: the method comprises the following steps:

step S1: using a white light source to illuminate the DMD, projecting a pattern generated by the DMD onto the surface of an object to be detected through a microscope objective, controlling a piezoelectric ceramic micro-step moving object to realize vertical scanning through an upper computer program, synchronously acquiring a group of imaging pictures carrying object height information by the CCD, converting the imaging pictures into digital signals and storing the digital signals into a computer;

step S2: evaluating the focus value of a pixel point in each image by using a focus evaluation algorithm to obtain a focus evaluation function value curve of the pixel point;

step S3: extracting the peak value position of a focus evaluation function value curve, taking the peak value position as the rough focusing position of a pixel point, and further positioning the accurate focusing position by combining a Gaussian curve fitting algorithm;

step S4: and repeating the operation, and traversing all the pixel points to obtain the corresponding accurate focusing positions so as to obtain the three-dimensional appearance of the object.

2. The structured light micro-nano three-dimensional morphology method based on the focusing evaluation function, which is characterized in that: and in the step S1, the object is illuminated by the structured light to increase the surface texture information of the object, so that the method is suitable for measuring the object with the coexisting smooth and rough surfaces, the object is vertically scanned, the picture is analyzed by using the focusing evaluation algorithm in the step S2, a focusing evaluation function value curve of the pixel point is obtained, and the position of the maximum value is the focusing position.

3. The high-precision micro-nano three-dimensional measurement method based on the time domain phase shift algorithm according to claim 1, which is characterized in that: in step S3, the scanning position where the peak of the focus evaluation function curve is located is extracted and a gaussian curve fitting algorithm is combined to obtain the position where the pixel point is accurately focused, so as to obtain the height information of the pixel point.

4. The structured light three-dimensional measurement method based on the time domain phase shift algorithm as claimed in claim 1, 2 or 3, wherein: the method combines a structured light illumination and focusing evaluation algorithm, obtains a pixel point focusing evaluation function value curve through vertical scanning and focusing degree analysis, and further combines a Gaussian curve fitting algorithm to position an accurate focusing position so as to obtain the three-dimensional shape of an object.

Technical Field

The invention belongs to the technical field of optical measurement engineering, and particularly relates to a structured light micro-nano three-dimensional morphology measurement method based on a focusing evaluation algorithm.

Background

In recent years, with the rapid development and strong promotion of new technologies, technologies in the field of micro-nano structures are continuously developed and advanced, and requirements for high precision and high reliability of microstructure surface morphology measurement are gradually improved in research directions such as the manufacturing of micro-structures such as micro-electro-mechanical systems and micro-optical elements, and the observation of cells in the biological field. The surface topography of the object not only affects the mechanical and physical properties of the contact parts, but also affects the properties of the non-contact surfaces, such as the reflection of optical devices, etc. The measurement of the structure is a prerequisite for understanding the structural properties and for quality assurance of the processing of the structure, so that the measurement of the surface topography plays a crucial role in the fields of materials, properties and functions of engineering parts and biomedicine, etc. Therefore, the requirement on the measurement precision of the micro-nano structure is higher and higher, and the micro-nano surface topography measurement technology is greatly developed.

The surface topography measurement is widely applied to the relevant fields of cutter detection, precision machining, material science, electronic industry, biomedicine and the like, particularly in the fields of ultra-precision machining and micro-electro-mechanical system manufacturing, along with the development of ultra-precision machining technology, a microstructure is gradually expanded from a workpiece with a simple structure and a regular shape to a workpiece with a complex structure and an irregular shape, and the surface topography measurement with high precision and high reliability on the microstructure is more and more important. The surface three-dimensional shape of the microstructure can obviously influence the reliability and the service performance of a device, and can reflect the quality of workpiece processing so as to improve the quality of the workpiece. Therefore, the improvement of the surface measurement technology has important significance for ensuring high performance and high stability of the product.

Currently available microstructure measurement methods can be divided into non-optical and optical measurement methods. The optical measurement method is widely applied to the advantages of high precision, high efficiency, no damage and the like. The existing optical measurement methods include laser confocal method, white light interference method, focusing evaluation function method and the like. The laser confocal method utilizes a point detector to measure an object point by point, and has high precision but low efficiency. The white light interference method measures an object by utilizing the principle that the white light coherence length is short, has high precision and high speed, but cannot measure the object which changes slowly and severely. The structured light micro-nano three-dimensional topography profiling based on the focusing evaluation algorithm is combined with the structured light illumination and focusing evaluation algorithm, the structured light is projected onto the surface of an object, a PZT scanning table scans the object longitudinally, a CCD collects a group of pictures carrying height information of the object and analyzes the pictures by using the focusing evaluation algorithm to obtain a focusing evaluation function value curve of a pixel point, and further a Gaussian curve fitting algorithm is combined to obtain the accurate focusing position of the pixel point so as to restore the three-dimensional topography of the object.

Disclosure of Invention

The invention designs a structured light micro-nano three-dimensional morphology measurement method based on a focusing evaluation algorithm, completes the work of theoretical analysis, algorithm recovery evaluation, simulation and the like, and verifies the feasibility of the method. The method has the advantages of simple measurement system, no damage, high efficiency, wide application and the like, and has wide application prospect.

In order to achieve the purpose, the technical scheme provided by the invention is as follows: a structured light micro-nano three-dimensional topography measuring method based on a focusing evaluation algorithm comprises the following steps:

step S1: and a white light source lighting system is used for projecting the pattern generated by the DMD onto the surface of the object to be detected, the PZT micro-step vertical scanning of the object to be detected is controlled by an upper computer program, and the CCD synchronously acquires an imaging picture and converts the imaging picture into a digital signal to be stored in a computer.

Step S2: and analyzing the collected pictures by using a focus evaluation algorithm, and calculating a focus evaluation function value of the pixel point in each picture to obtain a focus evaluation function value curve, wherein the peak position of the focus evaluation function value curve is the focus position of the pixel point.

Step S3: and extracting a scanning position where the peak value of the focus evaluation function value curve is located, taking the scanning position as the rough focal plane position of the pixel point, and combining a Gaussian curve fitting algorithm to obtain the accurate focusing position of the pixel point.

Step S4: and recovering the three-dimensional appearance of the object after the accurate focusing position of each pixel point is obtained.

The focusing degree of the pixel points is changed by vertically scanning an object and synchronously acquiring an imaging picture, and the picture is analyzed by using a focusing evaluation algorithm to obtain a focusing evaluation function value curve, wherein the position of the maximum value is the focusing position.

The scanning position of the peak value of the focus evaluation function value curve is extracted and a Gaussian curve fitting algorithm is combined to obtain the accurate focusing position of the pixel point, and then the height information of the pixel point is obtained, so that the three-dimensional appearance of the object can be restored.

The basic principle of the invention is as follows: the structured light is projected to the surface of an object, a PZT scanning table scans the object longitudinally, a CCD collects a group of pictures carrying height information of the object and analyzes the pictures by using a focusing evaluation algorithm to obtain a focusing evaluation function value curve of a pixel point, and a Gaussian curve fitting algorithm is further combined to obtain the accurate focusing position of the pixel point so as to restore the three-dimensional appearance of the object.

The focusing evaluation function is constructed according to the fact that the better the focusing is, the more the picture contains detailed information, the larger the gray gradient is represented in a space domain, and the more high-frequency components are represented in a frequency domain.

The projection of the structured light onto the surface of the object is to increase the texture information of the surface of the object, so that the focusing evaluation algorithm is more sensitive. Theoretically, when a pixel point is at a focus position, the gray gradient of the field is the largest, so that the focusing degree of the pixel point is judged according to the gray gradient.

Compared with the prior art, the invention has the advantages that:

(1) compared with the interferometric measurement, the method is a non-interferometric measurement method, so that the influence between layers is less, and the method is suitable for detection of more multilayer structures.

(2) Compared with a confocal measurement method, the method adopts a surface measurement mode, so that the efficiency is higher and the system structure is simpler.

(3) Compared with the traditional measuring method based on the focusing evaluation algorithm, the method combines the structured light illumination, increases the texture information of the object surface, and can be suitable for the measurement of the object with the coexistence of the smooth surface and the rough surface.

(4) The method has the advantages of simple measuring system, no damage, high efficiency, wide application and the like.

Drawings

FIG. 1 is a schematic view of a measurement system, wherein: the system comprises a white light source 1, a digital micromirror array (DMD)2, a tube lens I3, a CCD (charge coupled device) acquisition system 4, a tube lens II 5, a spectroscope 6, a microscope lens 7 and a piezoelectric ceramic scanning Platform (PZT) 8.

FIG. 2 is a flow chart of a structured light micro-nano three-dimensional measurement method based on a focus evaluation algorithm disclosed by the invention.

Fig. 3 is a curve of the focus evaluation function value of a certain pixel.

Fig. 4 is a simulated object map and a restored map, in which fig. 4(a) is a simulated object topography map, fig. 4(b) is a restored object topography map, and fig. 4(c) is an error map.

Detailed Description

For the purpose of making the objects, aspects and advantages of the present invention more apparent, the present invention will be described in further detail below with reference to the accompanying drawings in conjunction with specific examples.

The invention discloses a structured light micro-nano three-dimensional measurement method based on a focusing evaluation algorithm, which utilizes a measurement system light path diagram as shown in figure 1, a white light source 1 is used for illuminating a digital micromirror array (DMD)2, a light beam irradiates the surface of an object to be measured through a tube lens I3, a spectroscope 6 and a microscope lens 7, wherein the DMD is positioned at the focal plane position of the tube lens I, the light path after the reflection of the surface of the object passes through a tube lens II 5, an imaging picture carrying the height information of the object is acquired by a CCD acquisition system 4, wherein the CCD is positioned at the focal plane position of the tube lens II, finally, the object is longitudinally scanned and synchronously acquired and imaged through a piezoelectric ceramic scanning table (PZT)8, and the acquired picture is focused and analyzed so as to recover the three-dimensional appearance of the object.

As shown in fig. 2, the structured light three-dimensional measurement method based on the focus evaluation algorithm disclosed by the invention comprises the following specific implementation steps:

step S1: and a white light source lighting system is used for projecting the pattern generated by the DMD onto the surface of the object to be detected, the PZT micro-step vertical scanning of the object to be detected is controlled by an upper computer program, and the CCD synchronously acquires an imaging picture and converts the imaging picture into a digital signal to be stored in a computer.

Step S2: and analyzing the collected pictures by using a focus evaluation algorithm, and calculating a focus evaluation function value of the pixel point in each picture to obtain a focus evaluation function value curve, wherein the peak position of the focus evaluation function value curve is the focus position of the pixel point.

Step S3: and extracting a scanning position where the peak value of the focus evaluation function value curve is located, taking the scanning position as the rough focal plane position of the pixel point, and combining a Gaussian curve fitting algorithm to obtain the accurate focusing position of the pixel point.

Step S4: and recovering the three-dimensional appearance of the object after the accurate focusing position of each pixel point is obtained.

Among them, the configuration of the focus evaluation function is the most critical factor determining the measurement accuracy. The principle is that the better the focus is, the clearer the picture is, the richer the detail information is, the larger the gray gradient is represented in the space domain, and the more the high-frequency components are represented in the frequency domain. The method calculates the focusing value of the pixel point by using the commonly used improved Laplace energy and function in the airspace so as to represent the focusing degree of the pixel point.

The modified laplacian operator is:

wherein f (x, y) represents the gray value of the pixel point. The modified laplacian operator, which is discrete in the spatial domain, can be represented as:

the laplace energy sum function can be expressed as:

wherein M and N represent the processing field of the selected pixel points. Equation (3) was used to calculate the focus merit function value for (x, y) in each plot, resulting in a focus merit function value curve as shown in fig. 3. And (4) extracting an accurate focusing position by combining a Gaussian curve fitting algorithm, and traversing all pixel points to restore the three-dimensional appearance of the object. To demonstrate the feasibility of this approach, simulation was performed on MATLAB, and the recovery and error comparisons are shown in fig. 4.