Fast Image Processing Algorithms Research Articles

Long-Distance, Real-Time LED Display-Camera Communication System Based on LED Point Clustering and Lightweight Image Processing

LED displays can be used to realize the dual functions of display and communication simultaneously. However, existing LED display-based visible light communication (VLC) systems suffer due to their short transmission distance and are not practical. A long-distance, real-time display-camera communication (DCC) system is proposed in this paper. First, a LED-DCC point clustering scheme is proposed to increase the transmission distance by clustering multiple adjacent LED display points for improving the quality of the VLC signal captured by an image sensor. Then, a lightweight, back-forth, fast image processing algorithm is proposed to reduce the introduced additional computational complexity caused by point clustering and enhance the reliability of information extraction from the real-time captured images/video frames. The experimental system was implemented with a 2.2-inch 16 × 16 point LED display and the CMOS camera on the smartphone. Experimental results show that the proposed system can achieve a maximum data transmission distance of 7 m under a bit error rate (BER) of 0.5, which is about 9 times that of the previous LED-DCC system, and can achieve a data transmission distance of 175 cm under the 7% forward error correction (FEC) limit, which is about 12 times that of the previous LED-DCC system. Additionally, the decoding latency for extracting information from each video frame is only 13.26 ms, which guarantees real-time data reception.

Spectrum classification of citrus tissues infected by fungi and multispectral image identification of early rotten oranges

Citrus fruit is susceptible to postharvest rot by fungal infection. The detection of early rot is difficult due to similar skin characteristics to sound area, which limits the ability of the grading system to evaluate the comprehensive quality of citrus. In this study, the visible and near infrared hyperspectral imaging system with the wavelength range of 325–1000 nm was used to collect hyperspectral images of oranges. Hyperspectral data of three types of tissues including sound tissue from 80 samples, rotten tissue infected by Penicillium digitatum from 100 samples and rotten tissue infected by Penicillium italicum from 100 samples were extracted. The bootstrapping soft shrinkage (BOSS) and BOSS-SPA (BOSS-Successive Projections Algorithm) combination algorithm were separately used to optimize spectrum variables. The partial least squares discriminant analysis (PLS-DA) model for classifying three types of tissues and PLS-DA model for classifying two types of tissues (sound tissue and rotten tissue) were constructed based on full-spectrum and the selected informative variables. Model comparisonshowed that the BOSS-PLS-DA model can effectively identify three types of tissues with the classification accuracy of 97.1%, while the BOSS-SPA-PLS-DA model was more effective for the binary classification of sound and rotten citrus tissues with the accuracy of 100%. Furthermore, the wavelength images corresponding to the nine informative variables extracted by BOSS-SPA were performed the principal component analysis (PCA), and four feature wavelength images (508, 568, 578 and 614 nm) were obtained by analyzing the weighting coefficients of each single-wavelength images constituting the optimal principal component (PC) image. Finally, a fast multispectral image processing algorithm combined with the global threshold theory was proposed for the rotten orange detection based on the extracted four wavelength images. A total of 280 samples including 80 sound and 200 rotten samples were used to evaluate the classification ability, which showed the proposed multispectral image detection algorithm can successfully differentiate between sound and rotten oranges with an overall classification accuracy of 98.6%.

Real-time display camera communication system based on LED displays and smartphones.

Visible light communication based on display and camera can simultaneously provide the functionalities of display and invisible information transmission. There are widely potential applications in information broadcasting, stealth advertising, etc. In this paper, a real-time display camera communication system based on LED displays and smartphones is proposed. To solve the rate mismatch problem and the symbol unsynchronization problem between the LED display panel with a relatively high frame rate and the smartphones' camera with a relatively low frame rate, we propose an Alternate Bit-flipping Repeat Coding scheme for adjustable frame rate matching and symbol synchronization with the advantage of eliminating flickers perceivable to human eyes. Fast image processing algorithms are also designed to decrease the computational complexity of extracting information from the captured video frames in real-time. An experimental system was implemented on a 16×16 points LED display panel with a refresh rate of 150 fps and a commercial Android smartphone with an 8 megapixels camera working at 30 fps and a self-developed Android APP. The experimental results show that the real-time LED display camera communication system can achieve a data transmission rate of 30 bps for one LED display point and a maximum distance of 80 cm, and the computational time on the Android smartphone for data receiving is only 11.827 ms.

Fast Primary Image Processing Algorithms in On-Board Vision Systems

Fast Primary Image Processing Algorithms in On-Board Vision Systems

Research and Hardware Design of Image Processing Algorithm Based on FPGA

With the continuous development of computer technology and microelectronics technology, image processing technology is constantly being improved, especially real-time image processing technology has been studied by a large number of scholars. This article aims to achieve the purpose of FPGA-based fast image processing through the research of FPGA’s fast image processing algorithm. Based on the advantages of FPGA high-speed hardware computing and parallel computing, this paper proposes a design based on FPGA parallel dual template strategy, and designs a comparative experiment to verify. Obtain objective evaluation indexes of image processing results through experiments, and analyze the data results. The experimental results show that: the implementation of the mean filter algorithm based on FPGA parallel dual templates, the time required is about half that of the mean filter algorithm based on FPGA single templates. Relative to the reference Matlab software programming method to achieve 678 times performance improvement. It shows that the realization method of the mean filter algorithm based on FPGA parallel dual template is feasible. Give full play to the advantages of FPGA parallel processing data, improve the processing speed of the image algorithm module.

Fast Median Filter Image Processing Algorithm and Its FPGA Implementation

Fast Median Filter Image Processing Algorithm and Its FPGA Implementation

In-situ control of microdischarge characteristics in unipolar pulsed plasma electrolytic oxidation of aluminum

Microdischarges occurring during plasma electrolytic oxidation are the main mechanism promoting oxide growth compared to classical anodization. When the dissipated energy by microdischarges during the coating process gets too large, high-intensity discharges might occur, which are detrimental to the oxide layer. In bipolar pulsed plasma electrolytic oxidation a so called ‘soft-sparking’ mode limits microdischarge growth. This method is not available for unipolar pulsing and for all material combinations. In this work, the authors provide a method to control the size- and intensity distributions of microdischarges by utilizing a multivariable closed-loop control. In-situ detection of microdischarge properties by CCD-camera measurements and fast image processing algorithms are deployed. The visible size of microdischarges is controlled by adjusting the duty cycle in a closed-loop feedback scheme, utilizing a PI-controller. Uncontrolled measurements are compared to controlled cases. The microdischarge sizes are controlled to a mean value of and , respectively. Results for controlled cases show, that size and intensity distributions remain constant over the processing time of 35 minutes. Larger, high-intensity discharges can be effectively prevented. Optical emission spectra reveal, that certain spectral lines can be influenced or controlled with this method. Calculated black body radiation fits with very good agreement to measured continuum emission spectra (). Variance of microdischarge size, emission intensity and continuum radiation between consecutive measurements is reduced to a large extent, promoting uniform microdischarge and oxide layer properties. A reduced variance in surface defects can be seen in SEM measurements, after coating for 35 minutes, for controlled cases. Surface defect study shows increased number density of microdischarge impact regions, while at the same time reducing pancake diameters, implying reduced microdischarge energies compared to uncontrolled cases.

A novel optical apparatus for the study of rolling contact wear/fatigue based on a high-speed camera and multiple-source laser illumination.

Rolling contact wear/fatigue tests on wheel/rail specimens are important to produce wheels and rails of new materials for improved lifetime and performance, which are able to operate in harsh environments and at high rolling speeds. This paper presents a novel non-invasive, all-optical system, based on a high-speed video camera and multiple laser illumination sources, which is able to continuously monitor the dynamics of the specimens used to test wheel and rail materials, in a laboratory test bench. 3D macro-topography and angular position of the specimen are simultaneously performed, together with the acquisition of surface micro-topography, at speeds up to 500 rpm, making use of a fast camera and image processing algorithms. Synthetic indexes for surface micro-topography classification are defined, the 3D macro-topography is measured with a standard uncertainty down to 0.019 mm, and the angular position is measured on a purposely developed analog encoder with a standard uncertainty of 2.9°. The very small camera exposure time enables to obtain blur-free images with excellent definition. The system will be described with the aid of end-cycle specimens, as well as of in-test specimens.

Inspection of Polymer Polaroid’s Visual Defects with Stripe Light Illumination

The visual defects of the polymer polaroid have a direct and serious influence on the quality of TFT-LCD panels. A variety of image detection systems have been proposed and widely used by the manufacturers of polaroid and panels in order to detect the visual defects at the earliest possible stage in the production process. Some slight visual defects, however, are barely visible in the images acquired by a camera when under a common illumination condition. In order to deal with this problem, we present a novel machine vision system in which a stripe light source is introduced to illuminate the polaroid sample, and these special defects therefore become more visible. At the base of the aforementioned image enhancement, a straightforward and fast image processing algorithm is designed and implemented. The Morphology Template Method is investigated and the shapes, the locations and the sizes of the visual defects are extracted successfully. The experimental results demonstrate this methodology’s validity to inspect the visual defects of transparent multilayer polymer films.

Robust image processing for an omnidirectional camera-based smart car door

Over the last decade, there has been an increasing emphasis on driver-assistance systems for the automotive domain. In this article, we report our work on designing a camera-based surveillance system embedded in a “smart” car door. Such a camera is used to monitor the ambient environment outside the car, for instance, the presence of obstacles such as approaching cars or cyclists who might collide with the car door if opened—and automatically control the car door operations. This is an enhancement to the currently available side-view mirrors that the driver/passenger checks before opening the car door. The focus of this article is on fast and robust image processing algorithms specifically targeting such a smart car door system. The requirement is to quickly detect traffic objects of interest from grayscale images captured by omnidirectional cameras. While known algorithms for object extraction from the image processing literature rely on color information and are sensitive to shadows and illumination changes, our proposed algorithms are highly robust, can operate on grayscale images (color images are not available in our setup), and output results in real time. We present a number of experimental results based on image sequences captured from real-life traffic scenarios to demonstrate the applicability of our algorithm.

General Structure Design for Fast Image Processing Algorithms Based upon FPGA DSP Slice

Abstract Increasing the speed and accuracy for a fast image processing algorithms during computing the image intensity for low level 3x3 algorithms with different kernel but having the same parallel calculation method is our target to achieve in this paper. FPGA is one of the fastest embedded systems that can be used for implementing the fast image processing image algorithms by using DSP slice module inside the FPGA we aimed to get the advantage of the DSP slice as a faster, accurate, higher number of bits in calculations and different calculated equation maneuver capabilities. Using a higher number of bits during algorithm calculations will lead to a higher accuracy compared with using the same image algorithm calculations with less number of bits, also reducing FPGA resources as minimum as we can and according to algorithm calculations needs is a very important goal to achieve. So in the recommended design we used as minimum DSP slice as we can and as a benefit of using DSP slice is higher calculations accuracy as the DSP capabilities of having 48 bit accuracy in addition and 18 x 18 bit accuracy in multiplication. For proofing the design, Gaussian filter and Sobelx edge detector image processing algorithms have been chosen to be implemented. Also we made a comparison with another design for proofing the improvements of the accuracy and speed of calculations, the other design as will be mentioned later on this paper is using maximum 12 bit accuracy in adding or multiplying calculations.

Large-Scale Automated Identification and Quality Control of Exfoliated and CVD Graphene via Image Processing Technique

Graphene, a monolayer of carbon atoms, is a high-interest material in the research community and semiconductor industry due to its extraordinary electronic, thermal, and mechanical properties. Graphene layer identification is very important since its intrinsic properties change drastically between each 0.34-nm thick layer. Current methods of identification rely on restrictive small-area microscopy techniques, the most robust being micro-Raman spectroscopy. Here we present a new method for a large-area graphene layer identification characterized by low cost, high accuracy, high throughput, complete automation, and scalability. Our metrology tool is based on a fast image processing algorithm, which analyzes optical contrasts between single-layer, bi-layer, and few-layer graphene used for exfoliated, transferred, or grown graphene flakes on large wafers verified by micro-Raman spectroscopy.

Absolute interfacial distance measurements by dual-wavelength reflection interference contrast microscopy.

Dual-wavelength reflection interference contrast microscopy (DW-RICM) is established as a microinterferometric technique to measure absolute optical distances between transparent planar substrates and hard or soft surfaces such as colloidal beads or artificial and biological membranes, which hover over the substrate. In combination with a fast image processing algorithm the technique was applied to analyze the trajectories of colloidal beads sedimenting under gravity. As the beads approach the surface of the substrate, they slow down because of hydrodynamic coupling of the bead motion to the substrate. The effective surface friction coefficients were measured as a function of the absolute distance of the beads from the surface. The height dependence of the friction coefficient was found to be in quantitative agreement with previous theoretical predictions. Furthermore, we demonstrate that the DW-RICM technique allows the determination of the height of membranes above substrates and the amplitude and direction of height fluctuations. Without any further need to label the membrane the unambiguous reconstruction of the surface profile of soft surfaces is possible.

作業の教示とプログラミング １ｍｓビジュアルフィードバックシステムのための高速対象追跡アルゴリズム

Most conventional visual feedback systems using CCD camera are restricted by video rates and therefore cannot be adapted to the changing environment sufficiently quickly. To solve this problem we developed a 1 ms visual feedback system using a general purpose massively parallel processing vision system in which photo-detectors and processing elements are directly connected. For high speed visual feedback fast image processing algorithms are also required. In particular, the difference of images between frames is very small in our system because of its high speed frame rate. Using this feature, we can realize several image processing techniques by simpler algorithms.In this paper we propose a simple algorithm for target tracking using the feature of high speed vision, and realize target tracking on the 1 ms visual feedback system.

Radar synthetic vision system for adverse weather aircraft landing

A synthetic vision system (SVS) is described for aid in landing aircraft in poor weather conditions. The system consists of a scanning millimeter wave radar, heads-up display and real-time signal processing hardware. A suite of fast image processing algorithms are used for enhancing and displaying of the imagery. The system has been tested in number of tower and flight demonstration during actual adverse weather conditions. The significance of the work is in both system demonstration of the overall concept and the novelty of its signal processing algorithms.

Algorithm for Purkinje images I and IV and limbus centre localization

To develop a fast and reliable image processing algorithm for the extraction of Purkinje reflection data for measurement of ocular alignment with standard PC hardware. Purkinje images I and IV are specular reflections of light sources, the positions of which are proportional to eye rotation. Fast histogram-based thresholding and gradient techniques were used to localize Purkinje images I and IV, the pupil centre and the limbus centre in images obtained with near infrared light. Execution time was 500 ms per eye. A set of 540 images was evaluated of which 94% were automatically analysed.

“Finger-Pointer”: Pointing interface by image processing

We have developed an experimental system for the 3D direct pointing interface “Finger-Pointer,” which can recognize finger pointing actions and simple hand forms in real-time by processing the image sequences captured by stereoscopic TV cameras. The operator is not required to attach any peculiar device such as the Data-Glove or a magnetic sensor. Simple and fast image processing algorithms employed in the system enable real-time processing without any special image processing hardware. By introducing the notion of “VPO (Virtual Projection Origin),” the system can recognize pointing actions stably and accurately regardless of the operator's pointing style. The system also synchronizes and integrates the audio and the visual channels by introducing the “Timing Tag” technique.

Machine identification of buds in images of plant shoots

Tissue cultures find increasingly widespread applications for cloning of many plants. Commercial propagation by tissue cultures is limited to ornamental plants, because the cost of skilled labor required cannot compete with conventional propagation methods. To cut down the cost, some automation is essential. A cost-effective approach is to chop the plantlets into segments on a conveying production line while using machine vision for identifying and locating the number and positions of propagation organs in images of the plantlet segments. Plantlet segments without propagation organs will be rejected, while segments with viable buds will be selected for subculturing. To this end, a machine-vision-controlled automatic subculturing system for potato tissue cultures is proposed as a simpler and more cost-effective solution than the popular trend of imitating the manual sub-culturing task by a robot. A simple and relatively fast image-processing algorithm particularly suitable for classification of potato tissue cultures, was developed. In lieu of the general Medial Axis Transform approach, this specialized algorithm takes advantage of the inherent difference between the geometrical shape and gray scale levels of the stems and the leaves as well as of the rather simple connectivity rules of attachment between them. The results indicate that machine inspection and classification of tissue culture plantlets is possible, but considerably more work needs to be done before this technique is fully developed for automating tissue culture processes.

Defining shapes with a fast image processing algorithm

With future robotic systems likely to hinge in part on the quality of their associated video image processing, a system has been evolved in which interior and exterior profiles of objects seen by a video camera can be computed in real time.