Auto Focus Research Articles

Study of Microscope Autofocus Based on Weighted Light Intensity

Microscopes auto focusing is critically important for a great spectrum of scientific and industrial applications. Finding the best focus position for variety of surfaces under measurement proved to be challenging. In order to provide a rapid and accurate method for microscope focusing positioning, a laser focus deviate system was employed for microscope focusing position. The relationship between focusing sensitivity and the surface under measurement was investigated. First, the laser focus deviate technique is introduced in light of characteristic parameters such as the diameter of the focused spot, the laser wavelength and the distance from the optimal focus. Then, the focusing displacement versus spot position curve fitting is performed for a smooth isotropic surface to directly locate the best focusing position. Following, it is analyzed that when applied to anisotropic and rough surfaces, the centroid of the image spot after reflection/scattering from the surface will deviate from its original light intensity distribution, thus deviate from the calculated optimal focus position and cause focusing errors. Finally, a criterion of weighted light intensity value Q is introduced to achieve fast focusing of anisotropic surfaces in combination with the laser focusing deviate technique. The experimental results show that for a 20× microscope objective system, the focusing accuracy of this focusing positioning method is 1.7 μm on smooth surfaces; and is at the micro meter level for rough surfaces. It basically meets the requirements for rapid, stable and reliable microscope auto focusing needs.

Microscope Autofocus Method Based on Analog Image Video Signal Processing

<p style="text-align: justify;"><span style="font-family: "times new roman";">The most important part of the automatic control microscope system is the auto focus technology. How to improve the accuracy and speed of the focus is the most noteworthy breakthrough point, in which the focus evaluation function is used to evaluate whether the image is correctly focused. Objective: through the evaluation of several kinds of focus evaluation functions, and according to the application of microscope focus technology in the research, we compare and select the focus method which is more easy to use image video signal for proper processing, and analyze and experiment the key technology. Methods: according to the high frequency component of image video signal, the class divergence of the difference between class samples, choosing the appropriate evaluation function and step size through the gradient value size, comparing the sharpness and edge of the focus image and the non-focus image to evaluate the quality and clarity of image video signal, selecting a high comprehensive auto focus algorithm to realize auto focus The gray difference method, Laplace operator and other evaluation functions. Results: in the end, the resolution of the image is 93.1%, and the success rate of auto focusing is 98.2%. The method based on analog image video signal processing improves the precision and speed of focusing, and it has been successfully applied to the auto focusing system of microscope.</span>

Optimizing Method of Autofocusing Function in Infrared Imaging System

In order to realize high efficiency auto focusing function in infrared imaging system,the characteristics of infrared imaging systems are analyzed.The optimization methods of auto-focusing functions in infrared imaging systems are discussed and summarized.Combined with practical engineering applications,a method for estimating the local random fluctuation noise of the image sharpness evaluation function is proposed.The method improves the reliability of automatic focusing processes.By introducing the sensitivity of image sharpness evaluation function as feedback into the climbing process,the convergence speed of the climbing algorithm can be optimized.The optimization methods were applied to engineering applications,and its implementation verified the correctness of the design and the effectiveness of the optimization methods.

Not All Webcams Are Created Equal [From the Screen of Stone

Almost all laptops computers and tablets have built-in webcams. However, most of these have 720p resolution (the equivalent of "standard definition" for television). A web cam with 1080p HD ("high definition") resolution will yield a noticeably sharper image, particularly for the situations that are common in video conferencing where the face fills most of the frame. Furthermore, that 1080p resolution needs to be supported at a 60 Hz refresh rate. Slower refresh rates (e.g., the 30 Hz rates used by some webcams) result in "jerky" motions when the person moves. A good webcam will have an auto focus feature. This keeps the face (or whatever else is the primary object in the field of view) automatically in focus regardless of the distance from the camera or of any motion. Many webcams also come with software that allows zooming and centering the image.

Macro-to-micro positioning and auto focusing for fully automated single cell microinjection

The automation methods and technologies of the single cell micro-injection reported in the literature have the common assumption that both the cell and the microtools has already been positioned within the microscopic field of view and well-focused. However, moving the microtools and biological cells from the macro field of view (macro-FOV) into the micro field of view (micro-FOV), and then further moving down into the culture medium and focusing were conducted manually and proved to be time consuming. In this work, we present algorithms and methods to automate this process. An electrothermal microgripper is used for picking and holding a zebrafish embryo instead of traditional micropipette. In order to position the microgripper into the micro-FOV, an extra macro camera is employed such that the microgripper jaws are under the macro-FOV. The micro-FOV is searched by moving the microgripper jaws in a serpentine path and zigzag path, respectively, and the grid-line identification algorithm is proposed to recognize the microgripper jaws that appear in the micro-FOV. Then, a contact detection algorithm is used to determine whether the gripper jaws are in the culture medium or not. Finally, eight algorisms are evaluated and compared to select the algorism with the best performance for auto-focusing the microgripper jaws in the culture medium. Up to 100 experiments are conducted to validate the proposed method for the macro-to-micro positioning and auto focusing of the microgripper jaws with the success rate 100% and 90%, respectively.

Correction of out-of-FOV motion artifacts using convolutional neural network

PurposeSubject motion during MRI scan can result in severe degradation of image quality. Existing motion correction algorithms rely on the assumption that no information is missing during motions. However, this assumption does not hold when out-of-FOV motion happens. Currently available algorithms are not able to correct for image artifacts introduced by out-of-FOV motion. The purpose of this study is to demonstrate the feasibility of incorporating convolutional neural network (CNN) derived prior image into solving the out-of-FOV motion problem. Methods and materialsA modified U-net network was proposed to correct out-of-FOV motion artifacts by incorporating motion parameters into the loss function. A motion model based data fidelity term was applied in combination with the CNN prediction to further improve the motion correction performance. We trained the CNN on 1113 MPRAGE images with simulated oscillating and sudden motion trajectories, and compared our algorithm to a gradient-based autofocusing (AF) algorithm in both 2D and 3D images. Additional experiment was performed to demonstrate the feasibility of transferring the networks to different dataset. We also evaluated the robustness of this algorithm by adding Gaussian noise to the motion parameters. The motion correction performance was evaluated using mean square error (NMSE), peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM). ResultsThe proposed algorithm outperformed AF-based algorithm for both 2D (NMSE: 0.0066 ± 0.0009 vs 0.0141 ± 0.008, P < .01; PSNR: 29.60 ± 0.74 vs 21.71 ± 0.27, P < .01; SSIM: 0.89 ± 0.014 vs 0.73 ± 0.004, P < .01) and 3D imaging (NMSE: 0.0067 ± 0.0008 vs 0.070 ± 0.021, P < .01; PSNR: 32.40 ± 1.63 vs 22.32 ± 2.378, P < .01; SSIM: 0.89 ± 0.01 vs 0.62 ± 0.03, P < .01). Robust reconstruction was achieved with 20% data missed due to the out-of-FOV motion. ConclusionIn conclusion, the proposed CNN-based motion correction algorithm can significantly reduce out-of-FOV motion artifacts and achieve better image quality compared to AF-based algorithm.

Design of a 5 degree of freedom–voice coil motor actuator for smartphone camera modules

Consumers pay most attention to the camera function of smartphones. Thus, manufacturers focus on improving the capabilities of camera modules to deliver clearer and sharper images to consumers. Today, camera modules with auto focusing (AF) and optical image stabilization (OIS) functions are standard in the industry. Specifically, OIS is of the linear movement and rotational movement types. In contrast to the rotational movement type, the commonly used linear movement type cannot compensate for rotational error. Therefore, this paper proposes a novel voice coil motor (VCM) actuator that can supply a 5 degree of freedom (DOF)–compensation that consists of three linear movements and two rotational movements for smartphone camera modules. This novel VCM actuator with 5-DOF compensation is realized using an innovative electromagnetic structure. This paper further verifies the properties of the proposed VCM actuator with a laboratory-built prototype. The experimental results verify the robust properties and feasibility of the proposed VCM actuator.

Polarization insensitive all-dielectric metasurfaces for the ultraviolet domain

In recent years, metasurfaces have provided a tempting path to replace conventional optical components where an abrupt phase change is imposed on an incident wave using a periodic array of unit cells. Till date, highly efficient dielectric metasurfaces have been demonstrated in infrared and visible domains. However, due to the lower bandgap of typical dielectric materials, such metasurfaces present strong absorption in the ultraviolet (UV) domain, and thus, hamper their realization at shorter wavelengths. In this paper, we utilize a large bandgap dielectric material, niobium pentoxide (Nb2O5), to construct an ultra-thin and compact transmission-type metasurface that manipulates the phase of an incident wave using an array of Nb2O5 nano-cylinder. By the virtue of numerical optimization, complete 2π phase coverage along with the high transmission efficiency (around 88.5%) is achieved at 355nm. Such efficient control over the phase of the incident wave enabled us to realize the polarisation insensitive self-accelerating parabolic, reciprocal, and logarithmic Airy beams (ABs) generating metasurfaces with the efficiency of 70%, 72% and 77%, respectively. In addition to this, we also demonstrate auto focusing Airy optical vortex (AFAOV) generators where the metasurfaces are designed to combine the phase profiles of an abruptly focusing Airy (AFA) beam and that of spiral phase plate (SPP). The AFAOV is generated with efficiency of 70% (for l = 3) and 72% (for l = 5).

Automatic Compensation for Defects of Laser Reflective Patterns in Optics-Based Auto-Focusing Microscopes

Since the optomechatronic system is characterized by a high energy density and high response speed, system performance can be substantially improved by integrating optical components with electromechanical systems. For micro-processing, conventional machining has been commonly replaced with laser processing. Auto-focusing plays a crucial role in processing, so developing an autofocus (AF) system with high precision and speed is vital. AF modules integrated with the knife edge method typically use a reflective semicircular laser image to calculate the defocus distance for the optical instrument and evaluate the accuracy. On the stage of an optical instrument, a reflective image is typically not a standard semicircular segment because of the different reflection characteristics of objects or the positioning error of the devices. In this study, a novel method is proposed to automatically compensate for these defects and errors. In addition to the compensation part, the improved adaptive anisotropic diffusion filter and wavelet-based edge detection are both proposed for pattern smoothing and enhancement, and pattern edge detection. For reflective patterns obtained using an image sensor in an optics-based AF module, the proposed method, compared with six state-of-the-art approaches in terms of several metrics, such as compensation accuracy, sensitivity, specificity, Dice coefficient, mean absolute distance, Hausdorff distance, and speed / computation time, enables and facilitates accurately reconstructing the complete semicircular segment. Experimental results show that the proposed method yields more satisfactory, stable and accurate results in comparison with six other approaches in performance analysis and statistical evaluation.

Next Generation Autofocus and Optical Image Stabilization System for Camera Modules Using Magnetic Shape Memory Actuators

Currently, camera modules are used in a wide range of applications ranging from micropo-sitioning actuator systems used in smartphones to larger modules used in stationary cameras, CCTV, and others. Modern camera modules are required to perform positioning functions to improve the stability and quality of captured images. These functions mainly include the autofocus (AF) and optical image stabilization (OIS) functions. Traditionally, separate actuators and sensors are used for AF and OIS, each contributing towards energy consumption, module size, and manufacturing costs. This is particularly disadvantageous in the case of smartphones owing to their inherent space and battery charge limitations. This paper presents a novel Magnetic Shape Memory (MSM) actuator system that combines the AF and OIS functions, which are performed using two actuators; thus, this system is a simple, compact, and cost-effective solution to the drawbacks of conventional technology. Furthermore, the smart properties of MSM alloys reduce the energy consumption of these systems through the utilization of their inherent holding forces and the associated shape memory effect. The realization of AF and OIS functions is discussed and verified experimentally for the proposed actuator system using data obtained from a fabricated prototype.

Passive Autofocusing System for a Thermal Camera

Most of the Thermal (Infrared) cameras nowadays are equipped with a motorized lens for focusing a scene manually. The subjective nature of manual focusing makes it an inefficient and cumbersome process. In contrast, Autofocusing (AF) obtains the best focused image based on a quantitative measure with the benefits of convenience and intelligence. Various AF systems for visual cameras have been developed, but relatively less amount of work has been done for thermal imaging systems. This paper presents a Vision and Control based Autofocusing System (VCAFS) comprising: (1) an uncooled thermal camera with motorized lens, (2) a passive contrast-based focus measure, (3) a smoothing operator to avoid local extrema, and (4) two different lens motion controllers. Experimental results show the efficacy of the proposed system on live videos even when the scene and its depth are continuously changing.

Design of Wide Angle and Large Aperture Optical System with Inner Focus for Compact System Camera Applications

Conventionally, a bright, very wide-angle optical system is designed as a floating type optical system that moves two or more lens groups composed of multiple lens in order to focus accurately. These have been widely used as phase detection auto focus (AF) methods within conventional digital single-lens reflex (DSLR) cameras. However, a phase detection AF optical system cannot be used when recording motion pictures. In contrast, a compact system camera (CSC) performs AF by the contrast method, where a stepper motor is used as the driving source for moving the optical lens. Nonetheless, to ensure that the focusing lens is lighter, these stepper motors should not have high torque and AF must be possible by moving only one lens. Yet, when focusing is performed with only one lens, aberration change due to focusing lens movement is magnified. Therefore, a very wide-angle optical system comprised of a half-angle of view more than 40 degrees and F of 1/4 has not been developed. Here, a very wide-angle optical system was designed with high resolving power that enables high speed AF, even in contrast mode, by moving only one lens while minimizing aberration change.

Whole slide imaging system using deep learning-based automated focusing.

The auto focusing system, which involves moving a microscope stage along a vertical axis to find an optimal focus position, is the chief component of an automated digital microscope. Current automated focusing algorithms, especially those deployed in cost effective microscopy systems, often cannot match the efficiency of a skilled human operator in keeping a sample in focus. This work presents an auto focusing system that utilises the recent advances in machine learning, namely deep convolutional neural networks (CNN). It improves upon prior work in this domain. The results of the focusing algorithm are demonstrated on an open data set. We describe the practical implementation of this method on a low cost digital microscope to create a whole slide imaging system (WSI). Results of a clinical study using this WSI system are presented. The study demonstrates the efficacy of this system in a practical scenario.

Deep Neural Network for Better Face Processing

This Paper represents the face detection using advanced method deep neural network which uses deep learning frame work. The old models used to detect the faces were like Haar-cascade method which detect the faces with good approaches but there is some uncertainty in the accuracy of the old models, so in this system we will use the latest deep neural network model which is embedded with latest open cv and by using the deep learning model frame work which is weighted with some other files. By using this model, we can achieve the better accuracy in face detection which can be used for further purposes like auto focus in cameras, counting number of people etc. This model detects the faces accurately and paves the way for better recognition systems which can be used in many face biometric applications. For this purpose, low-cost computer board Raspberry Pi and Camera Sensor will be used.

Generalized spot auto-focusing method with a high-definition auto-correlation function in transmission electron microscopy.

The spot auto-focusing (AF) method with a unique high-definition auto-correlation function (HD-ACF) proposed in the previous paper is improved and is now applicable to general specimens at a wide range of magnifications. According to the definition where the AF is defocused to obtain the highest resolution, the proposed method achieves the sharpest HD-ACF profile in the AF spot image. The relationship where the sharpest HD-ACF profile gives the highest resolution is theoretically explained, and practical AF examples for different specimens and magnifications are experimentally demonstrated. Specimens include a yeast cell thin section at 10-k magnification, a standard grating replica used as a ruler at 50-k, a crystal lattice of graphitized carbon at 400-k and a 60°-tilted thin section (yeast cell) at 10-k. Different procedures are prepared to actively identify the defocus position that gives the sharpest HD-ACF profile. Every AF result demonstrates the highest-resolution image.

Investigation of Gainp Quantum Dots in the AlGaInP-Based Light Emitting Diodes

Recently, AlGaInP-based light emitting diodes (LEDs) have experienced an impressive evolution in both device performance and market volume. However, development of new applications is required in order to realize their full potential in areas such as use as a light source for auto focusing in digital cameras, special illumination for particular functions in agriculture, and in full color displays. To enlarge their utility in these applications, it is necessary to fabricate and understand a new structure capable of emitting longer wavelengths of around 700 nm. In particular, AlGaInP heterostructure LEDs are lattice-matched with respect to the GaAs substrate, which limits the emitting spectrum to around 650 nm at the longer peak wavelength side. To fabricate an LED structure capable of emitting at a 700 nm peak wavelength, the composition (x) of GaxIn1-xP material in the active layer requires a compressive strain of larger than 1 %. This large lattice mismatch, however, causes significant problems in terms of both growth and device properties due to the formation of defects. To overcome these problems, it is necessary to relieve the well strain via the formation of islands, referred to as a Stranski-Krastanow (S-K) growth mode, in order to prevent the generation of dislocations [1,2]. However, in AlGaInP-based LEDs emitting at a 700 nm peak wavelength, the effects of well strain on the epitaxial growth and the realization of device performance has yet to be extensively studied. In this study, we investigate the behaviors of morphological and optical characteristics on the composition of Ga0.33In0.67P material and demonstrate the performance of a device emitting at around 700 nm using quantum dot (QD)-based LEDs. Figure 1

Ultrawide-angle optical system design for light-emitting diode-based ophthalmology and dermatology applications.

BACKGROUND: Compared to laser, light-emitting diodes – non-coherent and divergent light sources requires that the developed optical system support steering and focusing of light on the desired target when acquiring information regarding human tissues.OBJECTIVE: A new optical system with an ultrawide angle was designed to cover large areas of the eye, including facial areas near the eye, in order to overcome the limited field of view of optical systems used for ophthalmology and dermatology applications.METHODS: To achieve a compact and handheld optical system for ophthalmology and dermatology applications, a contrast auto-focus (AF) method must be used, and the weight reduction of the AF group is considered during the design process to satisfy the effective focal length (EFL), back focal length (BFL), and front focal length (FFL) in the proposed optical system using Gaussian-bracket method.RESULTS: The designed optical system can focus from infinity to a magnification of 0.19 times, representing a distance of 114.359 mm from the first surface of the optical system to the object. The AF lens moving distance from infinity to the minimum distance is approximately 4.984 mm. The full width at half maximum (FWHM) values of the red, green, and blue light-emitting diodes were 16 mm, 35 mm, and 22 mm, respectively.CONCLUSIONS: We have designed an ultrawide-angle optical system for compact optical systems that are suitable for high-performance ophthalmology and dermatology applications.

Auto-focusing approach on multiple micro objects using the prewitt operator

In this paper, we propose an auto focusing method to find the best plane of focus amongst different depth micro objects. By achieving this, the ultimate goal of the project will be autofocusing on motile micro-organisms to check their quality, e.g., semen motility. Firstly, the auto focusing system cycles through the rough focal range of the micro objects, which represents the cell culture by moving in steps of 2 $$\upmu \hbox {m}$$ towards best focus, passing it, and completing the scanning process. Simultaneously, at each step, an image of the sample is collected and transformed by use of a Prewitt edge detection operator in order to ascertain focal quality. Secondly, the system moves to the best focus position that is calculated via Prewitt edge detection approach. Thirdly, to begin actively monitoring the focal plane, the system makes minute adjustments to keep the target objects in-focus. This accounts for any changes in the culture, such as cells moving in and out of the focal window or up and down within the semen fluid. The Prewitt operator is tested for focusing performance on multi-microobjects at different focal planes and is compared with other edge detection gradient functions to confirm superiority.

High-definition and high-sensitivity CMOS image sensor with all-pixel image plane phase-difference detection autofocus

In this paper, we describe an overview of autofocus (AF) technology for digital still cameras, video camcorders, and smartphones. Subsequently, we propose a CMOS image sensor (CIS) with all-pixel image plane phase-difference detection AF (PDAF) and describe a device structure and an optical design for fast and high-quality AF and low-noise imaging. To perform both PDAF and imaging function in all pixels, an individual pixel is composed of two horizontally displaced sub-photodiodes (PDs) and one microlens (ML). In particular, we describe PD and pixel isolation technology for high-definition, high-sensitivity, and low-noise PDAF-CIS with about front-side-illuminated (FSI) 6.4-µm-size pixel and back-side-illuminated (BSI) 1.X µm-size pixels.

Autofocusing Technique Based on Generalized Multilayer Stolt Migration

A method is proposed for estimation of geometric information (GI) for obliquely layered geometry. The GI is estimated in the process of autofocusing (AF) of a ground-penetrating radar image. A novel AF technique is proposed based on the generalized multilayer Stolt migration algorithm. In the algorithm, the position and angle of the layer boundaries are determined using a Hough transform. At each layer, the AF metric is iteratively evaluated to estimate the relative permittivity (RP) of the layer. The performances of four AF metrics are compared, and an RP determination algorithm is suggested to reduce the number of AF metric evaluations. The proposed algorithm is validated with numerical and experimental data.