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Articles 1 - 29 of 29
Full-Text Articles in Engineering
Quantitative Assessment And Characterization Of Tool Wear Phenomena In Advanced Manufacturing Processes, Oybek Valijonovich Tuyboyov
Quantitative Assessment And Characterization Of Tool Wear Phenomena In Advanced Manufacturing Processes, Oybek Valijonovich Tuyboyov
Technical science and innovation
This paper explores the quantitative assessment and characterization of tool wear phenomena in advanced manufacturing processes, employing a multifaceted approach encompassing traditional measurements, image processing, machine learning, and predictive modeling. The study emphasizes the intricate dynamics of tool wear and its direct impact on cutting tool performance, addressing challenges in real-time monitoring and optimization of machining operations. Traditional methods like VBmax measurement are juxtaposed with advanced techniques such as the improved conditional generative adversarial net with a high-quality optimization algorithm (CGAN-HQOA), efficient channel attention destruction and construction learning (ECADCL), and shape descriptors based on contour, moments, orientations, and texture. Artificial …
Uncovering And Mitigating Spurious Features In Domain Generalization, Saeed Karimi, Hamdi̇ Di̇bekli̇oğlu
Uncovering And Mitigating Spurious Features In Domain Generalization, Saeed Karimi, Hamdi̇ Di̇bekli̇oğlu
Turkish Journal of Electrical Engineering and Computer Sciences
Domain generalization (DG) techniques strive to attain the ability to generalize to an unfamiliar target domain solely based on training data originating from the source domains. Despite the increasing attention given to learning from multiple training domains through the application of various forms of invariance across those domains, the enhancements observed in comparison to ERM are nearly insignificant under specified evaluation rules. In this paper, we demonstrate that the disentanglement of spurious and invariant features is a challenging task in conventional training since ERM simply minimizes the loss and does not exploit invariance among domains. To address this issue, we …
A Uav Target Tracking And Control Algorithm Based On Siamrpn, Songming Jiao, Hui Ding, Yufei Zhong, Xin Yao, Jiahao Jiahao Zheng
A Uav Target Tracking And Control Algorithm Based On Siamrpn, Songming Jiao, Hui Ding, Yufei Zhong, Xin Yao, Jiahao Jiahao Zheng
Journal of System Simulation
Aiming at the requirement of autonomously tracking land moving targets of rotary-wing UAVs, an autonomous and stable UAV tracking and control system that can adapt to the common interference environments such as scale changes, occlusions, and attitude changes is constructed.The system extracts the imaging position of the target in airborne camera through the twin network based on deep learning, and obtains the relative pose of the target. The image processing algorithm is designed to process the icons in the tracking frame, and the yaw angle of UAV relative to the tracking target is obtained, Kalman filter is introduced to …
Research On Visual Inspection Algorithm Of Crimping Appearance Defects For Wiring Harness Terminals, Bingan Yuan, Mingen Zhong, Jingxin Ni
Research On Visual Inspection Algorithm Of Crimping Appearance Defects For Wiring Harness Terminals, Bingan Yuan, Mingen Zhong, Jingxin Ni
Journal of System Simulation
Abstract: Aiming at the low efficiency and high missing rate of wiring harness terminals, an image detection method based on machine vision is proposed. The characteristic parameters of five typical defects in three main parts of wiring harness terminals are analyzed and defined. Tthe algorithms of extracting positioning datum, segmenting inspected-parts adaptively, extracting the defect features and calculating the characteristic parameters are designed respectively, and the defects criterions are given. The experimental results show that the algorithms are suitable for single defect and multi-class defects, both the miss detection rate and the false positiveness rate are low. The accuracy and …
A Novel Hybrid Decision-Based Filter And Universal Edge-Based Logical Smoothingadd-On To Remove Impulsive Noise, Rajanbir Singh Ghumaan, Prateek Jeet Singh Sohi, Nikhil Sharma, Bharat Garg
A Novel Hybrid Decision-Based Filter And Universal Edge-Based Logical Smoothingadd-On To Remove Impulsive Noise, Rajanbir Singh Ghumaan, Prateek Jeet Singh Sohi, Nikhil Sharma, Bharat Garg
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents a novel hybrid filter along with a universal extension to remove salt and pepper noise even at a very high noise density. The proposed filter initially specifies a threshold and then denoises the image using a combination of linear, nonlinear, and probabilistic techniques. Furthermore, to improve the quality, a universal add-on is presented which uses edge detection and smoothening techniques to brush out fine details from the restored image. To evaluate the efficacy, the proposed and existing filtering techniques are implemented in MATLAB and simulated with benchmark images. The simulation results show that the proposed filter is …
A Two-Stage Hair Region Localization Method For Guided Laser Hair Removal, Murat Avşar, İmam Şami̇l Yeti̇k
A Two-Stage Hair Region Localization Method For Guided Laser Hair Removal, Murat Avşar, İmam Şami̇l Yeti̇k
Turkish Journal of Electrical Engineering and Computer Sciences
Removal of hair using laser is a widely used method, where our goal is to permanently remove hair by using laser to cause heat in order to thermally damage the hair follicle. However, currently available laser hair removal systems affect the outer skin layers besides hair follicles. This is a disadvantage of classical methods with major health risks. We propose a method to overcome these health risks by guiding the laser beam only to automatically localized hair regions. This study aims to develop an automated feature-based hair region localization method as an integral part of the proposed hair removal system …
Image Processing Of Technological Objects, Lyudmila Petrovna Varlamova
Image Processing Of Technological Objects, Lyudmila Petrovna Varlamova
Chemical Technology, Control and Management
The article considers the problem of creating a smoke detection and fire detection system for technological objects. Fire detection is carried out using a vision system. Monitoring of technological objects is carried out using an unmanned aerial vehicle. For further actions, processing and classification of images is necessary. When observing the technological apparatuses of the chemical and petrochemical industry, problems arise associated with the large size, distribution and extent of objects. There may be situations in which there are violations of the technological regulations and, as a result, the occurrence of fire, fire and smoke. Using the technology of unmanned …
A Spatial Localization Of Structural Degradation Areas In The Single Crystal Turbine Blades By Means Of A Neutron Tomography Method, K. M. Nazarov, S. E. Kichanov, E. V. Lukin, A. V. Rutkauskas, B. N. Savenko
A Spatial Localization Of Structural Degradation Areas In The Single Crystal Turbine Blades By Means Of A Neutron Tomography Method, K. M. Nazarov, S. E. Kichanov, E. V. Lukin, A. V. Rutkauskas, B. N. Savenko
Eurasian Journal of Physics and Functional Materials
The single crystal nickel-based superalloy turbine blades have been studied by means of a neutron tomography method as a non-destructive structural probe. Di erences in neutron attenuation coe cients inside volume of metal bodies of the turbine blades have been found. Those observed di erences could be associated with inner structural incoherence areas arising in the process of operation of the turbine blades. Applications of special algorithms for a three-dimensional imaging data analysis allow obtaining a spatial distribution of those areas inside the turbine blades and estimate those volumes. To study a temperature evolution of structural incoherence areas, the additional …
Measurement Error Correction Model Of Tof Depth Camera, Le Wang, Luo Yu, Haikuan Wang, Minru Fei
Measurement Error Correction Model Of Tof Depth Camera, Le Wang, Luo Yu, Haikuan Wang, Minru Fei
Journal of System Simulation
Abstract: 3D data intuitively reflects the full view of the target or scene. Time of Flight (ToF) camera is a range imaging sensor that can provide 3D geometric information of targets immediately, thus it is widely applied in the robot positioning and navigation, 3D reconstruction and other aspects etc. Due to the operational principle of the camera itself, there are variety measurement errors of the source data obtained by ToF, resulting in image distortion. The measurement errors in the imaging process of ToF camera were analyzed and summarized, and the cubic spline interpolation method combined with look-up table was proposed …
Vehicle Logo Recognition Based On Sparse Sampling And Gradient Distribution Features, Binbin Zhou, Shangbing Gao, Zhigeng Pan, Liangliang Wang, Hongyang Wang
Vehicle Logo Recognition Based On Sparse Sampling And Gradient Distribution Features, Binbin Zhou, Shangbing Gao, Zhigeng Pan, Liangliang Wang, Hongyang Wang
Journal of System Simulation
Abstract: The vehicle logo location and recognition are separated in the traditional method, the location errors will affect the subsequent recognition, at the same time the vehicle logo images are with low resolution and poor quality. Thus, a novel method was proposed which integrated the vehicle logo location and recognition organically. The sample images were sampled by sparse sampling, and then the point set was divided into adjacent point set and non adjacent point set, and the gradient feature and light and dark feature were extracted respectively, constructing the feature library. The logo coarse location area was multi-scale scanned. The …
Image Denoising Using Deep Convolutional Autoencoder With Feature Pyramids, Ekrem Çeti̇nkaya, Mustafa Furkan Kiraç
Image Denoising Using Deep Convolutional Autoencoder With Feature Pyramids, Ekrem Çeti̇nkaya, Mustafa Furkan Kiraç
Turkish Journal of Electrical Engineering and Computer Sciences
Image denoising is 1 of the fundamental problems in the image processing field since it is the preliminary step for many computer vision applications. Various approaches have been used for image denoising throughout the years from spatial filtering to model-based approaches. Having outperformed all traditional methods, neural-network-based discriminative methods have gained popularity in recent years. However, most of these methods still struggle to achieve flexibility against various noise levels and types. In this paper, a deep convolutional autoencoder combined with a variant of feature pyramid network is proposed for image denoising. Simulated data generated by Blender software along with corrupted …
Block Form Of Kalman Filter In Processing Images With Low Resolution, Avazbek Marakhimov, Lyudmila Varlamova
Block Form Of Kalman Filter In Processing Images With Low Resolution, Avazbek Marakhimov, Lyudmila Varlamova
Chemical Technology, Control and Management
The article discusses the issues of preliminary processing and image filtering. One of the problems with image preprocessing is the presence of blurring and noise. The problem of highlighting the background of a moving object. Next, consider the problem of constructing a Kalman filter of block type. When using the Kalman filter to solve the adaptive filtering problem, the monitored process is the vector of optimal filter coefficients. The purpose of applying the Kalman filter is to minimize the variance of the estimate of the vector random process. Noise filtering in the form of a block filter allows to restore …
Accurate And Compact Stochastic Computations By Exploiting Correlation, Hamdan Abdellatef, Mohamed Khalil Hani, Nasir Shaikh-Husin
Accurate And Compact Stochastic Computations By Exploiting Correlation, Hamdan Abdellatef, Mohamed Khalil Hani, Nasir Shaikh-Husin
Turkish Journal of Electrical Engineering and Computer Sciences
Recent studies have shown, contrary to what was previously believed, that by exploiting correlation in stochastic computing (SC) designs, more accurate SC circuits with low area cost can be realized. However, if these basic SC circuits or blocks are cascaded in series to form a large complex system, correlation between stochastic numbers (SNs) from one block to the next would be lost; thus, inaccuracies are introduced. In this study, we propose correlating circuits to be used in building complex correlated SC systems. One of the circuits is the correlator that restores lost correlations between two SNs due to previous processing. …
A Multiseed-Based Svm Classification Technique For Training Sample Reduction, Imran Sharif, Debasis Chaudhuri
A Multiseed-Based Svm Classification Technique For Training Sample Reduction, Imran Sharif, Debasis Chaudhuri
Turkish Journal of Electrical Engineering and Computer Sciences
A support vector machine (SVM) is not a popular method for a very large dataset classification because the training and testing time for such data are computationally expensive. Many researchers try to reduce the training time of SVMs by applying sample reduction methods. Many methods reduced the training samples by using a clustering technique. To reduce its high computational complexity, several data reduction methods were proposed in previous studies. However, such methods are not effective to extract informative patterns. This paper demonstrates a new supervised classification method, multiseed-based SVM (MSB-SVM), which is particularly intended to deal with very large datasets …
Elimination Of Useless Images From Raw Camera-Trap Data, Ulaş Tekeli̇, Yalin Baştanlar
Elimination Of Useless Images From Raw Camera-Trap Data, Ulaş Tekeli̇, Yalin Baştanlar
Turkish Journal of Electrical Engineering and Computer Sciences
Camera-traps are motion triggered cameras that are used to observe animals in nature. The number of images collected from camera-traps has increased significantly with the widening use of camera-traps thanks to advances in digital technology. A great workload is required for wild-life researchers to group and label these images. We propose a system to decrease the amount of time spent by the researchers by eliminating useless images from raw camera-trap data. These images are too bright, too dark, blurred, or they contain no animals. To eliminate bright, dark, and blurred images we employ techniques based on image histograms and fast …
Hardware Implementation Of A Scale And Rotation Invariant Object Detection Algorithm On Fpga For Real-Time Applications, Murat Peker, Hali̇s Altun, Fuat Karakaya
Hardware Implementation Of A Scale And Rotation Invariant Object Detection Algorithm On Fpga For Real-Time Applications, Murat Peker, Hali̇s Altun, Fuat Karakaya
Turkish Journal of Electrical Engineering and Computer Sciences
A hardware implementation of a computationally light, scale, and rotation invariant method for shape detection on FPGA is devised. The method is based on histogram of oriented gradients (HOG) and average magnitude difference function (AMDF). AMDF is used as a decision module that measures the similarity/dissimilarity between HOG vectors of an image in order to classify the object. In addition, a simulation environment implemented on MATLAB is developed in order to overcome the time-consuming and tedious process of hardware verification on the FPGA platform. The simulation environment provides specific tools to quickly implement the proposed methods. It is shown that …
Some Properties Of Digital H-Spaces, Özgür Ege, İsmet Karaca
Some Properties Of Digital H-Spaces, Özgür Ege, İsmet Karaca
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, we study certain properties of digital H-spaces. We prove that a digital image that has the same digital homotopy type with any digital H-space is also a digital H-space. We show that the digital fundamental group of a digital H-space is abelian. We give examples that are related to a digital homotopy associative H-space and a $\kappa $-contractible digital H-space. Several important applications of digital H-spaces are given in computer vision and image processing. Finally, we deal with the importance of digital H-space in digital topology and image processing. We conclude that any $\kappa $-contractible digital image …
Brain Tumor Detection Using Monomodal Intensity Based Medical Image Registration And Matlab, Emrah Irmak, Ergun Erçelebi̇, Ahmet Hani̇fi̇ Ertaş
Brain Tumor Detection Using Monomodal Intensity Based Medical Image Registration And Matlab, Emrah Irmak, Ergun Erçelebi̇, Ahmet Hani̇fi̇ Ertaş
Turkish Journal of Electrical Engineering and Computer Sciences
digital image processing. Using suitable computer programming techniques and transformation between two images, a new much more informative image can be found. In this paper, three important and basic medical image registration (MIR) methods, namely MIR by maximization of mutual information, MIR using cross correlation (Fourier transform approach), and MIR by minimization of similarity metric, were proposed and accordingly two comprehensive applications were performed using MIR by minimization of the similarity metric, which uses the sum of the squared differences metric as a metric and the regular step gradient descent optimizer as an optimizer. What is more, MR images of …
Detection Of Microcalcification In Digitized Mammograms With Multistable Cellular Neural Networks Using A New Image Enhancement Method: Automated Lesion Intensity Enhancer (Alie), Levent Ci̇vci̇k, Burak Yilmaz, Yüksel Özbay, Gani̇me Di̇lek Emli̇k
Detection Of Microcalcification In Digitized Mammograms With Multistable Cellular Neural Networks Using A New Image Enhancement Method: Automated Lesion Intensity Enhancer (Alie), Levent Ci̇vci̇k, Burak Yilmaz, Yüksel Özbay, Gani̇me Di̇lek Emli̇k
Turkish Journal of Electrical Engineering and Computer Sciences
Microcalcification detection is a very important issue in early diagnosis of breast cancer. Generally physicians use mammogram images for this task; however, sometimes analyzing these images become a hard task because of problems in images such as high brightness values, dense tissues, noise, and insufficient contrast level. In this paper, we present a novel technique for the task of microcalcification detection. This technique consists of three steps. The first step is focused on removing pectoral muscle and unnecessary parts from the mammogram images by using cellular neural networks (CNNs), which makes this a novel process. In the second step, we …
A Wheeled Mobile Robot Path-Tracking System Based On Image Processing And Adaptive Cmac, Jih-Gau Juang, Ko-Jui Hsu, Chih-Min Lin
A Wheeled Mobile Robot Path-Tracking System Based On Image Processing And Adaptive Cmac, Jih-Gau Juang, Ko-Jui Hsu, Chih-Min Lin
Journal of Marine Science and Technology
This study entailed applying image-processing techniques and an intelligent control method to a wheeled mobile robot (WMR) for real-time trajectory recognition and tracking. The WMR was fitted with a charge-coupled device (CCD) camera to capture images of the environment, and the hue-saturationintensity color space was used to classify the color features of the captured images. The WMR calculates the relative position of a target object by using image-processing and edgedetection algorithms. This paper proposes a cerebellar model articulation controller (CMAC) and adaptive CMAC to replace conventional proportional-integral-derivative (PID) controller for guiding the WMR to track a desired path. Moreover, using …
Contrast Enhancement Using Linear Image Combinations Algorithm (Ceulica) For Enhancing Brain Magnetic Resonance Images, Burak Yilmaz, Yüksel Özbay
Contrast Enhancement Using Linear Image Combinations Algorithm (Ceulica) For Enhancing Brain Magnetic Resonance Images, Burak Yilmaz, Yüksel Özbay
Turkish Journal of Electrical Engineering and Computer Sciences
Brain magnetic resonance imaging (MRI) images support important information about brain diseases for physicians. Morphological alterations in brain tissues indicate the probable existence of a disease in many cases. Proper estimation of these tissues, measuring their sizes, and analyzing their image patterns are parts of the diagnosis process. Therefore, the interpretability and perceptibility level of the MRI image is valuable for physicians. In this paper, a new image contrast enhancement algorithm based on linear combinations is presented. The proposed algorithm is focused on improving the interpretability and perceptibility of the image information. An MRI image is presented to the algorithm, …
A Novel Fuzzy Filter For Speckle Noise Removal, Mehmet Ali̇ Soytürk, Alper Baştürk, Mehmet Emi̇n Yüksel
A Novel Fuzzy Filter For Speckle Noise Removal, Mehmet Ali̇ Soytürk, Alper Baştürk, Mehmet Emi̇n Yüksel
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a novel fuzzy system-based method for speckle noise removal is proposed. The proposed method consists of a fuzzy inference system, an edge detection and dilation unit, and an image combiner. The fuzzy inference system includes 5 inputs and 1 output, and it is responsible for filtering the speckle noisy image. The inputs of the fuzzy system consist of the center pixel of the filtering window and its 2 horizontal and vertical neighbors. The edge detection and dilation unit is used for classifying the uniform areas and nonuniform image regions such as edges. The image combiner unites the …
Spatiotemporal Realization Of An Artificial Retina Model And Performance Evaluation Through Isi- And Spike Count-Based Image Reconstruction Methods, İrfan Karagöz, Mustafa Özden
Spatiotemporal Realization Of An Artificial Retina Model And Performance Evaluation Through Isi- And Spike Count-Based Image Reconstruction Methods, İrfan Karagöz, Mustafa Özden
Turkish Journal of Electrical Engineering and Computer Sciences
Development of an artificial retina model that can mimic the biologic retina is a highly challenging task and this task is an important step in the development of a visual prosthesis. The receptive field structure of the retina layer is usually modeled as a 2D difference of Gaussian (DOG) filter profile. In the present study, as a different approach, a retina model including a 3D 2-stage DOG filter (3D-ADOG) that has an adaptively changing bandwidth with respect to the local image statistic is developed. Using this modeling, the adaptive image processing of the retina can be realized. The contribution of …
An Automated Prognosis System For Estrogen Hormone Status Assessment In Breast Cancer Tissue Samples, Fati̇h Sarikoç, Adem Kalinli, Hülya Akgün, Fi̇gen Öztürk
An Automated Prognosis System For Estrogen Hormone Status Assessment In Breast Cancer Tissue Samples, Fati̇h Sarikoç, Adem Kalinli, Hülya Akgün, Fi̇gen Öztürk
Turkish Journal of Electrical Engineering and Computer Sciences
Estrogen receptor (ER) status evaluation is a widely applied method in the prognosis of breast cancer. However, testing for the existence of the ER biomarker in a patient's tumor sample mainly depends on the subjective decisions of the doctors. The aim of this paper is to introduce the usage of a machine learning tool, functional trees (FTs), to attain an ER prognosis of the disease via an objective decision model. For this aim, 27 image files, each of which came from a biopsy sample of an invasive ductal carcinoma patient, were scanned and captured by a light microscope. From these …
Resolution Enhancement Of Video Sequences By Using Discrete Wavelet Transform And Illumination Compensation, Sara Izadpanahi, Çağri Özçinar, Gholamreza Anbarjafari, Hasan Demirel
Resolution Enhancement Of Video Sequences By Using Discrete Wavelet Transform And Illumination Compensation, Sara Izadpanahi, Çağri Özçinar, Gholamreza Anbarjafari, Hasan Demirel
Turkish Journal of Electrical Engineering and Computer Sciences
This research paper proposes a new technique for video resolution enhancement that employees an illumination compensation procedure before the registration process. After the illumination compensation process, the respective frames are registered using the Irani and Peleg technique. In parallel, the corresponding frame is decomposed into high-frequency (low-high, high-low, and high-high) and low-frequency (low-low) subbands using discrete wavelet transform (DWT). The high-frequency subbands are superresolved using bicubic interpolation. Afterwards, the interpolated high-frequency subbands and superresolved low-frequency subband obtained by registration are used to construct the high-resolution frame using inverse DWT. The superiority of the proposed resolution enhancement method over well-known video …
Change Detection Without Difference Image Computation Based On Multiobjective Cost Function Optimization, Turgay Çeli̇k, Zeki̇ Yetgi̇n
Change Detection Without Difference Image Computation Based On Multiobjective Cost Function Optimization, Turgay Çeli̇k, Zeki̇ Yetgi̇n
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, we propose a novel method for unsupervised change detection in multi-temporal satellite images by using multiobjective cost function optimization via genetic algorithm (GA). The spatial image grid of the input multi-temporal satellite images is divided into two distinct regions, representing ``changed'' and ``unchanged'' regions between input images, via the intermediate change detection mask produced by the GA. The dissimilarity of pixels of ``changed'' regions and similarity of pixels of ``unchanged'' regions between input multi-temporal images are measured using image quality metrics which consider correlation, spectral distortion, radiometric distortion, and contrast distortion. The contextual information of each pixel …
Design And Application Of An Image-Processing-Based Fuzzy Autopilot For Small-Boat Approaching Maneuvers, Sin-Der Lee, Ching-Yaw Tzeng, Young-Zehr Kehr, Chih-Kai Kang, Chi-Chun Huang
Design And Application Of An Image-Processing-Based Fuzzy Autopilot For Small-Boat Approaching Maneuvers, Sin-Der Lee, Ching-Yaw Tzeng, Young-Zehr Kehr, Chih-Kai Kang, Chi-Chun Huang
Journal of Marine Science and Technology
This paper presents an image-processing-based fuzzy autopilot scheme for accomplishing small-boat approaching maneuvers in a harbor environment. In the proposed approach, two canvas targets are arranged in cascade on the quayside to form a leading line. The targets are detected by a charge coupled device (CCD) camera mounted on the bow of the boat, and their geometric centers are computed by a Hue- and Saturation-based image-processing scheme. The autopilot system calculates the current heading deviation and tracking deviation angles of the boat by analyzing the displacements of the target centers relative to the CCD center line. These angles are then …
Development Of A Cost Effective Mini Autonomous Underwater Vehicle, Chiu-Feng Lin, Chyuan-Yow Tseng
Development Of A Cost Effective Mini Autonomous Underwater Vehicle, Chiu-Feng Lin, Chyuan-Yow Tseng
Journal of Marine Science and Technology
This paper describes the development of a cost effective mini autonomous underwater vehicle. The mini size of the vehicle is achieved by extracting the control module hardware out from the vehicle vessel and by reducing the on-board sensors. The control of the vehicle is conducted by a base station wirelessly telecommunicating with the vehicle. Furthermore, the reduction of the sensors also reduces the cost of the vehicle. For the purpose, in the vehicle, a single sensor featuring a CCD camera is mounted at the front of the vehicle. The images taken by this CCD camera are used both for obstacle …
Knowledge-Based Navigation For Autonomous Road Vehicles, Murat Eki̇nci̇, Franches W.J.Gibbs, Barry T. Thomas
Knowledge-Based Navigation For Autonomous Road Vehicles, Murat Eki̇nci̇, Franches W.J.Gibbs, Barry T. Thomas
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents a computer vision system for an autonomous road vehicle (ARV) that is capable of negotiating complex road networks including road junctions in real time. The ultimate aim of the system is to enable the vehicle to drive automatically along a given complex road network whose geometric description is known. This computer vision system includes three main techniques which are necessary for an ARV: a) road following, b) road junction detection, c) manoeuvring at the road junction. The road following algorithm presents a method of executing a number of algorithms using different methods concurrently, fusing their outputs together …