Real-time Image Processing Techniques Research Articles

Diagnosis of Diabetic Retinopathy using Fundus Images and Image Processing Methods

Abstract: Diabetes is a metabolic condition that causes organ failure, including retinal damage. Diabetic Retinopathy causes blindness by leaking blood vessel fluid into the retina also called as exudates. Thus, there has been a surge of interest in automated methods for detecting diabetic retinopathy using image processing techniques. Using real-time image dataset and image processing techniques, the proposed system is able to detect major retinal abnormalities such as enlarged retinal veins, blood spots, and white-yellow patches that indicate fluid leakage. The system analyses colour retinal images to determine the extent of damage and locate clusters of injured pixels within the region. The technique has a greater detection accuracy of 88%, and it has been demonstrated to be successful in detecting exudates and abnormalities from fundus images. In addition, the system is extremely helpful. To make suggestions for possible treatments based on an examination of the fundus images

Experimental characterization of a fast X-ray spectroscopic imager module using the ALTAIR P3 ASIC for real-time contaminants detection

X-ray imagers with spectroscopic capabilities and high photon count rates are finding promising applications in industrial real-time inspection systems. In this context, XSpectra® combines a CdTe-based linear energy-resolved photon counting (ERPC) pixel sensor with real-time image processing techniques to detect low and high density contaminants. The detection unit makes use of a new analog read-out ASIC that has been designed by Politecnico di Milano to meet strict application requirements both in energy resolution and achievable photon count rate. A room-temperature low-rate spectroscopic characterization of the system at a peaking time of 60 ns showed an average equivalent noise charge of 259 electrons r.m.s. (2.72 keV FWHM in CdTe) and an average FWHM of the 59.5 keV 241Am line of 3.6 keV, with a 3σ dispersion in noise performance of ±10% over 256 channels. The detection unit was tested in high incoming photon flux conditions by means of an X-ray tube. Minimal spectral distortion due to pile-up events is obtained up to an Incoming Count Rate of 2.5 Mcps/channel, while the maximum counting capability of energy-resolved events is 2.2 Mcps/channel.

Real-Time Image Processing and Computer Vision Techniques in Mechatronic Systems

Real-time image processing and computer vision techniques have become increasingly important in the field of mechatronic systems. Mechatronic systems integrate mechanical, electrical, and computer engineering to create advanced systems with enhanced functionality and performance. The integration of image processing and computer vision in mechatronic systems has opened up new possibilities for applications such as object detection, tracking, recognition, and robotic vision.This paper aims to provide an overview of the various real-time image processing and computer vision techniques employed in mechatronic systems. It explores the fundamental concepts, methodologies, and algorithms used in these techniques to extract meaningful information from images and videos, enabling mechatronic systems to make intelligent decisions based on visual inputs. The real-time image processing and computer vision techniques play a vital role in mechatronic systems, enabling intelligent decision-making based on visual inputs. This paper provides a comprehensive overview of these techniques, including their fundamental principles, implementation considerations, and practical applications. The advancements in real-time image processing and computer vision continue to push the boundaries of mechatronic systems, unlocking new possibilities and driving innovation in various industries

Automatic Channel Detection Using DNN on 2D Seismic Data

Geologists interpret seismic data to understand subsurface properties and subsequently to locate underground hydrocarbon resources. Channels are among the most important geological features interpreters analyze to locate petroleum reservoirs. However, manual channel picking is both time consuming and tedious. Moreover, similar to any other process dependent on human intervention, manual channel picking is error prone and inconsistent. To address these issues, automatic channel detection is both necessary and important for efficient and accurate seismic interpretation. Modern systems make use of real-time image processing techniques for different tasks. Automatic channel detection is a combination of different mathematical methods in digital image processing that can identify streaks within the images called channels that are important to the oil companies. In this paper, we propose an innovative automatic channel detection algorithm based on machine learning techniques. The new algorithm can identify channels in seismic data/images fully automatically and tremendously increases the efficiency and accuracy of the interpretation process. The algorithm uses deep neural network to train the classifier with both the channel and non-channel patches. We provide a field data example to demonstrate the performance of the new algorithm. The training phase gave a maximum accuracy of 84.6% for the classifier and it performed even better in the testing phase, giving a maximum accuracy of 90%.

Performance Improvement of Electro Optic Search and Track System for Maritime Surveillance

Surveillance of maritime domain is absolutely vital to ensure an appropriate response against any adverse situation relating to maritime safety or security. Electro-optic search and track (EOST) system plays a vital role by providing independent search and track of potential targets in marine environment. EOST provides real-time images of objects with details, required to neutralise threats. At long range, detection and tracking capability of EOST degrades due to uncertainty in target signatures under cluttered scenario. Image quality can be improved by using suitable sensors and enhancement using the target/background signature knowledge. Robust tracking of object can be achieved by optimising the performance parameters of tracker. In the present work, improvement in the performance of EOST subsystems such as sensor, video processor and video tracker are discussed. To improve EOST performance in terms of detection and tracking, sensor selection criterion and various real time image processing techniques and their selection criteria for maritime applications have been also discussed. Resultant improvement in the quality of image recorded under marine environment has been presented.

Closed-loop Control Using High Power Hexapole Magnetic Tweezers for 3D Micromanipulation

This paper presents the design, modeling, integration, and application of 3D printed high power hexapole magnetic tweezers for 3D micromanipulation applications. Six sharp-tipped magnetic poles were configured with electromagnetic coils and mounted on 3D printed magnetic yokes to form a tilted Cartesian coordinate system for actuation. A closed loop control algorithm was developed to automatically manipulate external power supplies connected to the magnetic tweezers, by using 3D positional information obtained from real-time image processing techniques. When compared against other designs of magnetic tweezers, our system has a larger working space and can generate higher magnetic field strengths. This allows for more diverse applications regarding small scale manipulation, including cell manipulation and cell therapy. Experiments and analytics explained in this paper demonstrate the closed-loop manipulation of micro-swimmers can provide a magnetic force as high as 800 pN while maintaining a positional error below 4 µm in 3D and 1.6 µm in 2D. Using the desired location as the control input, the microswimmers investigated were able to achieve arbitrary 2D and 3D trajectories. We also show that the implemented hexapole magnetic tweezers have adequate power to control microswimmers in Newtonian fluid environments. The system will later be optimized and deployed to control microswimmers in non-Newtonian fluid environments.

Nucleotide Identification in DNA Using Dielectrophoresis Spectroscopy.

We show that negative dielectrophoresis (DEP) spectroscopy is an effective transduction mechanism of a biosensor for the detection of single nucleotide polymorphism (SNP) in a short DNA strand. We observed a frequency dependence of the negative DEP force applied by interdigitated electrodes to polystyrene microspheres (PM) with respect to changes in both the last and the second-to-last nucleotides of a single-strand DNA bound to the PM. The drift velocity of PM functionalized to single-strand DNA, which is proportional to the DEP force, was measured at the frequency range from 0.5 MHz to 2 MHz. The drift velocity was calculated using a custom-made automated software using real time image processing technique. This technology for SNP genotyping has the potential to be used in the diagnosis and the identification of genetic variants associated with diseases.

Label-Free Biosensing Method for the Detection of a Pancreatic Cancer Biomarker Based on Dielectrophoresis Spectroscopy

We show that negative dielectrophoresis (DEP) spectroscopy is an effective transduction mechanism of a biosensor for the diagnosis and prognosis of pancreatic cancer using the biomarker CA 19-9. A substantial change in the negative DEP force applied to functionalized polystyrene microspheres (PM) was observed with respect to both the concentration level of the pancreatic cancer biomarker CA 19-9 and the frequency of the electric field produced by a pearl shaped interdigitated gold micro-electrode. The velocity of repulsion of a set of PM functionalized to a monoclonal antibody to CA 19-9 was calculated for several concentration cutoff levels of CA 19-9, including 0 U/mL and 37 U/mL, at the frequency range from 0.5 to 2 MHz. The velocity of repulsion of the PM from the electrode was determined using a side illumination and an automated software using a real-time image processing technique that captures the Mie scattering from the PM. Since negative DEP spectroscopy is an effective transduction mechanism for the detection of the cutoff levels of CA 19-9, it has the potential to be used in the early stage diagnosis and in the prognosis of pancreatic cancer.

Vision improvement system using image processing technique for adverse weather condition of opencast mines

This paper deals with a vision improvement system (VIS) developed using real-time image processing technique by CSIR-Central Institute of Mining and Fuel Research, Dhanbad aiming at providing comparatively clear vision to the operators of HEMM (Heavy Earth Moving Machinery) in foggy weather condition in opencast mines. It can also be used in deteriorated visibility situation due to mist, haze, smog, etc. while driving other vehicles also. In adverse weather, mining processes cannot be carried out during one-third of a day due to problem of perceptibility which reduces production rate of opencast mines. The developed system amplifies colour, sets the brightness and contrast to the input video to make objects more visible by reducing the effect of fog, mist, haze and smog. In order to enable quick real time operation, a fast CPU with dedicated graphics processing unit is used which is well suited for intensive data processing; because of its high computational efficiency and robustness, the developed system is able to operate at high frame rate and it is suitable for real-time driving assistance in adverse weather condition.

A new imaging technology to reduce the radiation dose during uterine fibroid embolization.

Uterine fibroid embolization (UFE) is a minimally invasive imaging-guided treatment using radiation exposure. To compare the patients' radiation exposure during UFE before and after introduction of a new X-ray imaging platform. Forty-one patients were enrolled in a prospective, comparative two-arm project before and after introduction of a new X-ray imaging platform with reduced dose settings, i.e. novel real-time image processing techniques (AlluraClarity). Demographic, pre-interventional imaging, and procedural data, including dose area product (DAP) and estimated organ dose on the ovaries and uterus, were recorded and angiographic quality of overall procedure was assessed. There were no significant differences in demographic characteristics and preoperative fibroid and uterine volumes in the two groups. The new imaging platform led to a significant reduction in mean total DAP (102 vs. 438 Gy.cm2; P < 0.001), mean fluoroscopy DAP (32 vs. 138 Gy.cm2; P < 0.001), mean acquisition DAP (70 vs. 300 Gy.cm2; P < 0.001), and acquisition DAP estimated organ dose in ovaries (42 vs. 118 mGy; P < 0.001) and uterus (40 vs. 118 mGy, P < 0.001), without impairment of the procedure and angiographic image quality. A substantial 77% reduction of DAP values and 64% and 66% reduction in organ dose on ovaries and uterus, respectively, was demonstrated with the new imaging platform, while maintaining optimal imaging quality and efficacy.

Real-time Multiresolution Crosswalk Detection with Walk Light Recognition for the Blind

Real-time image processing and object detection techniques have a great potential to be applied in digital assistive tools for the blind and visually impaired persons. In this paper, a ...

Computer-Based System for Simulating Visual Impairments

ABSTRACTThis paper presents the design, development, and preliminary evaluation of a computer-based system capable of simulating the consequences of several eye diseases in human vision. The system consists of a video camera, a computer, and a virtual reality (VR) helmet. Real-time image processing techniques are applied to the camera's video signal and the result is projected on the VR helmet. Upon the use of filters or masks, users can experience eye pathologies such as diabetic retinopathy, macular degeneration, hemianopsia, retinitis pigmentosa, among others. The system was evaluated by normally sighted in tasks such as reading and mobility. Results obtained allowed users to develop a greater awareness of the nature of visual impairments. The system is also intended to be used as a technological platform for testing assistive devices for visually impaired people.

Design and Evaluation of an Eye Disease Simulator

This paper presents the design, development, and preliminary evaluation of a computer-based system capable of simulating the consequences of several eye diseases in human vision. The system consists of a video camera, a computer, and a virtual reality (VR) helmet. Real-time image processing techniques are applied to the camera's video signal and the result is projected on the VR helmet. Upon the use of filters or masks, users can experience eye pathologies such as glaucoma, hemianopsia, macular degeneration, retinitis pigmentosa, among others. The system was validated by qualified experts and evaluated by healthy sighted in tasks such as reading and mobility. Results obtained allowed users to develop a greater awareness of the nature of visual impairments. The system is also intended to be used as a technological platform for testing assistive devices for visually impaired people.

참조 템플릿 기반 실시간 이동체 영상을 이용한 대안적 탐지 방안 - 주차관리시스템을 대상으로

주차장은 교통시스템의 일부분으로, 최근 차량이 급증하면서 주차장의 안전성과 효율적 운영이 중요해 지고 있다. 이동 차량을 탐지하여 주차 현황을 안내하기 위한 다양한 연구가 진행되어 왔지만 영상 내에 빠르게 이동하는 다수의 차량을 동시에 탐지하는 것은 여전히 도전적인 문제이다. 이에 본 연구에서는 공영 주차장이나 대형 주차장에 주차 구역이 분명하고 주차 구역 내에 감시 카메라가 설치되어있는 것에 착안하여, 참조 템플릿 기반 실시간 영상처리 기법을 이용한 무인 주차 가용 정보 제공 및 안내 시스템을 개발하고자 하였다. 즉, 주차 공간 내에 참조 표식 마커로써 주정차 중인 차량의 움직임과 상황을 인지하여 차량의 크기, 형태 등 직접적인 탐지 여부에 관계없이 주차 관제가 가능한 대안적 방법을 제시하였다. 또한, 주차 정보와 층별 주차 현황을 시뮬레이션하기 위한 프로토타입 시스템을 구현하여 본 연구에서 제시한 방법론의 실제 적용 가능성을 검토하고 성능 분석을 수행하였다. 결과적으로 실시간 영상 정보를 처리하여 주차장의 총 주차 공간 수, 주차된 차량 수와 같은 주차장 통계 정보의 저장 관리가 가능하였다. 향후, 본 연구 결과는 주차 상황 분석을 통해 주차 관리를 체계적이고 효율적으로 운영하는데 있어 비용 절감과 사용자 편의를 보다 증진 시킬 수 있을 것으로 기대된다. As the number of vehicles has been sharply increases, the significance of safety and effective operation issues in the parking lot is being emphasized, which takes a part of the transportation system. Recently, there have been several studies for the parking management by detecting moving object, however, recognizing numbers of fast-moving vehicles simultaneously in the picture is still a challenging problem. The parking lot in public area, or large-sized buildings has clear parking section, whereas the sensor system is configured to monitor a plurality of parking spaces. Therefore, by considering those parking lots, we suggested to develop the real-time parking availability information system by applying the real-time image processing techniques. with the help of template matching. Following the study, we wanted to provide the alternative method for parking management system through the reference template makers by recognizing movements of parked vehicles with the size and shape, regardless of direct detecting of driving movements. In addition, we evaluated the applicability and performances of the information system, presented in this study, and implemented a prototype system to simulate the parking statuses of each floor. In fat, it was possible to manage and analyze statistics about the total number of parking spaces and the number of vehicles parked through real-time video flames. We expected that the result of the study will be advanced, following the user-friendliness and cost reduction in operating parking management system and giving information by efficient analysis of parking situation.

Iterative deconvolution technique for measurements of diffraction-limited images on optical microscopes

Diffraction limit is usually a thorny problem in an optical inspection system. In this investigation, a model-based deconvolution technique was developed to recover diffraction-limited images, where images with sizes smaller than the diffraction limit could be recognized. Experiments were carried out with a traditional microscope at 200× magnification coupled with a halogen light source for a series of line width samples. The point spread function of the imaging optics was first obtained from an estimated model and then combined with a nonlinear deconvolution algorithm to calculate the full width at half maximum and reconstruct the line widths. Experimental results indicate that a measurement error below one pixel size of the measurement system is achievable. Accordingly, the target of nanoscale line width inspection based on a low cost and real-time image processing technique can be fulfilled, which greatly increases the ability of nanoscaling on optical microscopes.

Test bed for real-time image acquisition and processing systems based on FlexRIO, CameraLink, and EPICS

Image diagnostics are becoming standard ones in nuclear fusion. At present, images are typically analyzed off-line. However, real-time processing is occasionally required (for instance, hot-spot detection or pattern recognition tasks), which will be the objective for the next generation of fusion devices. In this paper, a test bed for image generation, acquisition, and real-time processing is presented. The proposed solution is built using a Camera Link simulator, a Camera Link frame-grabber, a PXIe chassis, and offers software interface with EPICS. The Camera Link simulator (PCIe card PCIe8 DVa C-Link from Engineering Design Team) generates simulated image data (for example, from video-movies stored in fusion databases) using a Camera Link interface to mimic the frame sequences produced with diagnostic cameras. The Camera Link frame-grabber (FlexRIO Solution from National Instruments) includes a field programmable gate array (FPGA) for image acquisition using a Camera Link interface; the FPGA allows for the codification of ad-hoc image processing algorithms using LabVIEW/FPGA software. The frame grabber is integrated in a PXIe chassis with system architecture similar to that of the ITER Fast Controllers, and the frame grabber provides a software interface with EPICS to program all of its functionalities, capture the images, and perform the required image processing. The use of these four elements allows for the implementation of a test bed system that permits the development and validation of real-time image processing techniques in an architecture that is fully compatible with that of the ITER Fast Controllers. This paper provides a specific example of a pattern search in a movie, its real-time implementation, and a performance analysis of the entire platform.

Special issue on architectures and techniques for real-time processing of remotely sensed images

Advances in sensor technology are revolutionizing the way remotely sensed images are collected, managed and processed. The incorporation of latest generation sensors to airborne and satellite platforms is currently producing a nearly continual stream of high-dimensional image data [6], and this explosion in the amount of collected information has rapidly created new processing challenges [4]. In particular, many current and future applications of remote sensing in Earth science, space science, and soon in planetary exploration science, require real or near realtime processing capabilities. Relevant examples include monitoring of natural disasters, such as earthquakes and floods, military applications, tracking of man-induced hazards, such as wild land and forest fires, oil spills and other types of biological agents. Most of these applications require timely responses for swift decisions, which depend on realtime performance of algorithm analysis. Owing to the diversity and large dimensionality of the image data sets provided by observation instruments in Earth and planetary applications, there are no commonly accepted real-time image processing architectures and techniques in the context of remote sensing missions. In future years, remote sensing imaging spectrometers [2] such as hyperspectraland ultraspectral imagers [1] will continue increasing their spatial and spectral resolutions (imagers with thousands of narrow spectral bands are currently under development), thus producing a nearly continual stream of high-dimensional image data [5] and increasing the possibility of exploitation of the data with regards to multi-spectral imagers [3]. Such technological advances are not only expected in optical remote sensing instruments, but also in radar and other types of remote sensing systems. Such explosion in the amount, size and dimensionality of the information collected on a daily basis presents new challenges for real-time processing in certain remote sensing applications, which demand for quick response in practical exploitation. This special issue on ‘‘Architectures and techniques for real-time processing of remotely sensed images’’ is intended to present the state of the art and the most recent developments in the incorporation of (near) real-time image processing techniques and specialized architectures in the context of remote sensing applications. This special issue covers different techniques and architectures for (near) real-time image processing in remote sensing. The techniques addressed in the special issue deal with relevant problems in Earth observation, such as damage mapping in case of earthquakes, flood monitoring, target and anomaly detection for military applications, cloud cover assessment or precision agriculture. The set of implementation strategies discussed in the special issue is also extensive, including parallel and distributed platforms, grid computing and multi-core environments, and specialized architectures for real-time on-board processing such as field programmable gate arrays (FPGAs) or commodity graphics processing units (GPUs). Combined these topics are expected to provide an excellent snapshot of the state of the art in those areas, and to offer a thoughtful perspective of the potential and emerging challenges of applying real-time image processing architectures and algorithms to realistic remote sensing problems. The special issue comprises eight articles contributed by authors with extensive experience in the field of efficient A. J. Plaza (&) Department Technology of Computers and Communications, Escuela Politecnica, University of Extremadura, Avenida de la Universidad s/n, 10071 Caceres, Spain e-mail: aplaza@unex.es URL: http://www.umbc.edu/rssipl/people/aplaza

Study on buoyancy convection phenomenon in the crystal growth process

Real-time phase shift Mach-Zehnder interference technique, imaging technique, and computer image processing technique were combined to perform a real-time diagnosis of NaClO3 crystal, which described both the dissolution process and the crystallization process of the NaClO3 crystal in real-time condition. The dissolution fringes and the growth fringes in the process were obtained. Moreover, a distribution of concentration field in this process was obtained by inversion calculation. Finally, the buoyancy convection phenomenon caused by gravity in the crystal growth process was analyzed. The results showed that this convection phenomenon directly influences the growth rate of each crystal face in the crystal.

Computer-aided experiment of using real-time small angle light scattering image processing technique for visual characterization flow field of polymer melts

The phenomenon of small angle light scattering (SALS) has been applied to the actual extrusion molding process. The current study utilizes a self-designed mold with built-in windows for observation of polymer melts within a slit die. A high-speed charge-coupled-device (CCD) camera is used to record the SALS images in real-time with different process conditions for subsequent analysis. Modification algorithm has been proposed to eliminate the effect of multiple scattering. Flow behavior of polymer melts is simulated and analyzed by real-time SALS image processing technique. Visualization is performed via a high-performance computer-aided analysis software which allows on-line data acquisition and characterization the flow field of polymer melts.

Combination of tissue harmonic sonography, real-time spatial compound sonography and adaptive image processing technique for the detection of carotid plaques and intima-medial thickness

Background and purpose Conventional sonography (CS) had many unwanted artifacts, which obscured the carotid artery lesions. We try to explore whether the combination of tissue harmonic imaging (THI), real-time spatial compound sonography (SCS), and adaptive image processing (AIP) techniques (CTX) could be a better way to reduce the artifacts in the carotid artery and enhance the visualization of its plaques and intima-medial thickness (IMT) than CS. Methods Eighty-three patients who harbored IMT (73) and carotid plaques (19) with variable degrees of stenosis underwent scanning for which five different ultrasound techniques were performed for overall image quality, lesion conspicuity, and elimination of artifacts. Two observers, who were blinded to the imaging techniques, graded the different images. A Friedman test was used for multiple statistical comparisons between the five techniques. To make paired comparisons between different imaging modes, Wilcoxon's signed-rank test was used. Results The mean Kappa score for the two independent observers was 0.812 (standard error, 0.021), and reflected moderate-to-high interobserver agreement. Combining SCS + THI + AIP (CTX) provided the best for overall image quality, lesion conspicuity, and elimination of undesired artifacts of carotid plaques whereas CS produced the worst quality ( p < 0.001). There were significant differences among the five techniques ( p < 0.001); however, there were no differences between SCS and THI on either image quality ( p = 0.417), lesion conspicuity ( p = 0.594), or elimination of artifact ( p = 0.064). Conclusions The combined technique of SCS, THI, and AIP may represent the optimal ultrasonic technique for the evaluation of the IMT and carotid plaque echomorphology.