Mehmet Celenk

Mehmet Celenk
Ohio University · Department of Electrical Engineering and Computer Science

Doctor of Philosophy (Ph.D.)

About

172
Publications
10,008
Reads
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930
Citations
Citations since 2016
18 Research Items
319 Citations
201620172018201920202021202201020304050
201620172018201920202021202201020304050
201620172018201920202021202201020304050
201620172018201920202021202201020304050
Additional affiliations
September 1985 - December 2016
Ohio University
Position
  • Professor

Publications

Publications (172)
Article
Full-text available
Multiple layers block overlapped histogram equalization (MLBOHE) is a classic image enhancement method. However, median filter is used in it to reduce noises which cause the degeneration of the local information. Moreover, the hidden details are not revealed effectively during the image fusion processes. To solve these drawbacks, an adaptive image...
Article
Full-text available
This study presents a novel image enhancement method in consideration of low contrast and blurred details of ultrasonic well logging images by combining the contrast limited adaptive histogram equalization (CLAHE) with power-law transformation. The red, green, and blue (RGB) color image is first transformed into hue, saturation, and intensity (HSI)...
Article
This paper deals with the theoretical aspect of bat echolocation and bionics, and image processing-based target recognition and identification methods. The state estimation methods utilizing the linear rustic filters such as fixed gain and Kalman filters are studied and implemented for echolocation bionics for estimating the LOS distance. A complet...
Article
Full-text available
Enabled by piezoceramic transducers, ultrasonic logging images often suffer from low contrast and indistinct local details, which makes it difficult to analyze and interpret geologic features in the images. In this work, we propose a novel partially overlapped sub-block histogram-equalization (POSHE)-based optimum clip-limit contrast enhancement (P...
Article
Full-text available
Advanced sensing technologies are providing for greater capabilities to discern and classify details of objects as they appear in actual environments as experienced by nonprofessional drivers. Distinctive geometric configurations of new sensory devices including but not limited to infrared (abbreviated as IR) and LIDAR sensory units are appearing a...
Article
Changes in morphology of a skin Iesion is indicative of melanoma, a deadly type of skin cancer. This paper proposes a temporal analysis approach to monitor the vascular appearance, the pigment structure, and growth of a skin Iesion. A set of digital images of a patients- skin Iesion acquired during follow-up imaging sessions serves as an input to o...
Chapter
Developing tactical or strategic methods to counter the small Unmanned Aerial System (sUAS) threats is effectively pacing up. With the advent of unprecedented proliferation of malicious or unintended intrusion from drones, the national infrastructure could be at risk and can become vulnerable if detection, tracking and disruption of these sUAS empl...
Conference Paper
Full-text available
Sensing techniques using varied configurations of infrared (IR) devices are rapidly becoming a proven approach for autonomous vehicles. In this paper, we present an investigation and corresponding results of embedding these sensors in a prototype robotic model and examine its performance. The results support IR sensing as a viable alternative to a...
Article
This paper aims to develop a vision-based driver assistance system for scene awareness using video frames obtained from a dashboard camera. A saliency image map is devised with features pertinent to the driving scene. This saliency map mimics the human contour and motion sensitive visual perception by extracting spatial, spectral, and temporal info...
Article
Rural roads present potential risks for drivers. One of them is horizontal curve, which poses higher risk than freeway. This is the major theme for the presented work here aiming to develop a model that predicts risk of curved roads. Major road geometry components associated with curve structure are road slope type being uphill or downhill, road cu...
Conference Paper
Breast cancer is one of the most common causes of death in women aged 40 and above. Early detection of breast cancer has been one of the prime topics of research in biomedical engineering area. Micro-calcifications (MCs) are the indicators of early stages of breast cancer, and the detection of these MCs will, in turn, lead to diagnosis and treatmen...
Article
In this work, we assess the detection and classification of specially constructed targets in coincident airborne hyperspectral imagery (HSI) and high spatial resolution panchromatic imagery (HRI) in spectral, spatial, and joint spatial–spectral feature spaces. The target discrimination powers of the data-level and feature-level fusion of HSI and HR...
Conference Paper
Previous work with the Bobcat 2013 data set¹ showed that spatial-spectral feature extraction on visible to near infrared (VNIR) hyperspectral imagery (HSI) led to better target detection and discrimination than spectral-only techniques; however, the aforementioned study could not consider the possible benefits of the shortwaveinfrared (SWIR) portio...
Article
In this study, we aim to determine fault severity in an electric car that may be caused by yawing due to such disturbances as non-uniform road pavements, in-wheel bearing clearance, suspension system, driver under Influence of alcohol (DUI), and tire deformation. The major research contribution herein is to alert drivers about an unforeseen situati...
Article
Full-text available
Diabetic retinopathy may potentially lead to blindness without early detection and treatment. In this research, an approach to automate the identification of the presence of diabetic retinopathy from color fundus images of the retina has been proposed. Classification of an input fundus image into one of the three classes, healthy/normal, Non-Prolif...
Conference Paper
As a vehicle proceeds on urban road that includes possible street players such as pedestrian, vehicles, traffic signs, traffic lights, or crosswalks, we can mention about holistic risk caused by dynamic behavior of each items moving along stochastic directions. In the numerous studies, traditional risk estimation methods have been devoted to utiliz...
Conference Paper
Rural and secondary roads inherently exhibit road curves and turns. This study aims to predict the risk associated with rural road curves exploiting major curve features such as curvature, slope type, and direction. The images acquired by rear and front cameras are utilized to capture the underlined features. Slope type is obtained by two-view imag...
Conference Paper
In this study, we investigate the regional risk estimation of drivers for street environment involving different players such as pedestrians, other vehicles, traffic signs, traffic lights, and crosswalks. Various researches focusing on objects regarding traffic have been realized by means of traditional risk estimation. In turn, conventional method...
Conference Paper
The amount of hyperspectral imagery (HSI) data currently available is relatively small compared to other imaging modalities, and what is suitable for developing, testing, and evaluating spatial-spectral algorithms is virtually nonexistent. In this work, a significant amount of coincident airborne hyperspectral and high spatial resolution panchromat...
Article
Research results reported in the literature underline the importance of color and textural variations of a skin lesion for accurate diagnosis of malignant skin cancer. Computer assistance for clinical prognosis is being increasingly utilized for early detection, which, in turn, significantly increases the chances of survival. This work with the use...
Conference Paper
In urban areas, safe and secure vehicle parking presents various problems as vehicles are driven at low speeds toward available parking spots. If there is an obstacle in front or back of the car, drivers have to accelerates their cars from zero to higher speed to pass over the obstruction. Obstacle could be curbs, bumper or any rim over the parking...
Conference Paper
In this research, the aim is to come up with an algorithm determining most appropriate variables of CAN (Controller Area Network) bus data for Aggressive/Calm Driving detection problem. This study assists drivers to take attention their Aggressive/Calm Driving habits on steering wheel. System complexity increases as involving all the variables in t...
Conference Paper
In this paper, we present an approach to the driver head motion tracking problem using Bayesian learning and inter-frame optical flow clustering. Two cameras (one operating in visual band and the other in the infra-red range) are mounted on vehicle dashboard to determine the driver head motion by examining the temporal variation of video-histogram...
Conference Paper
In the urban areas, drivers may need to step over obstacles for safety caution. At this stage, drivers have to slow down and move at low speed while passing over curbs. If there is an obstacle in front or back of the car, driver should step on the gas to speed up the car from zero to cautionary speed to pass over it. The obstacle in question could...
Conference Paper
In this study, our goal is to develop an algorithm for selecting most appropriate attributes of CAN (Controller Area Network) bus data in association with Uphill/Downhill road detection problem. In turn, drivers are made aware of Uphill/Downhill situations on steering wheel. In a sense, drivers are enabled to have optimal driving performance for ro...
Conference Paper
In this research paper, we describe a moving object detection algorithm in video frame sequences based on interframe temporal information and marked-watershed notion in the intra-spatial domain. The algorithm begins with difference image between two adjacent frames. By applying the Canny operator to the difference image and the current video frame,...
Conference Paper
In this paper, we propose a new model for 3-car interactive risky behavior of vehicles travelling in front and behind of a driver (overtaken) car. Following distance of vehicles moving in front and at rear end of the car in question plays an important role for overtaking scenario. Moreover, the distance between the car in front and the vehicle foll...
Article
This study introduces a hybrid method for deformable matching of Magnetic resonance (MR) images by utilizing the advantages of both wavelets and variational calculus. Image matching problem is expressed as an optimal control problem and discretization of the resulting Euler-Lagrange equations is written in terms of the system of linear equations in...
Conference Paper
Ultrasound images, though easy to obtain, have inherent flaws due to low frequency tissue image aberrations such as poor contrast caused by the presence of the granular speckle noise. The proposed algorithm aims to improve the ability to differentiate between healthy and malignant conditions via the use of homomorphic filtering and Otsu's gray-leve...
Article
Full-text available
This paper introduces several mathematical image registration models. Image registration, an ill-posed optimization problem, is formulated as the minimization of the sum of an image similarity metric and a regularization term. Curvature-driven diffusion-based techniques, in particular Perona-Malik, anisotropic diffusion, mean curvature motion (MCM)...
Article
Full-text available
In this paper, we present a new method for integration of 3-D medical data by utilizing the advantages of 3-D multiresolution analysis and techniques of variational calculus. We first express the data integration problem as a variational optimal control problem where we express the displacement field in terms of wavelet expansions and, secondly, we...
Conference Paper
This paper describes a new approach to analyze the spectral information of the samples of skin tissue that are localized in the spatial plane of microscopic image for discrimination of three different skin cancerous lesion prognoses. First, a cancerous lesion image is segmented from the skin surface based on Otsu's optimal histogram thresholding te...
Conference Paper
Here, we describe a method that detects vehicle(s) approaching from behind to a commuting car in the lane in which both are travelling. This research contributes to the development of driver assistance systems by means of informing them about the approaching traffic from behind and warn the drivers in case they are drowsy or not alert and the drivi...
Conference Paper
This paper describes a new method to discriminate between benign and malignant skin cancer samples obtained from the nevoscope which is one of the most commonly used skin imaging apparatus amidst an array of others including the electron microscope and the spectrometer. Although there have been various approaches in the literature proposed for skin...
Article
This paper describes the various methods that are implemented to diagnose a sample of skin for malignancy. Skin cancer detection at the earliest stage possible is vital to increase the chance of survival of the affected patient. Imaging in this field happens to be at the cross-roads. Skin cancer imaging can be visual in nature (nevoscope imaging, e...
Conference Paper
This paper describes a method that helps in detection of sun tanned or precancerous skin using gross-overall image segmentation and boundary tracing to localize three layers in human skin tissue. Skin cancer can become highly invasive and lethal if not treated at the earliest possible stage. The undertaken research herein aims to eliminate the need...
Article
Full-text available
One of the challenges in the development of image registration al-gorithms is their validation. In this article first we overview a recently proposed image registration method [2] and then assess its quality with validation strategies such as visual assessment, masked mean warping index and similarity metric. Secondly we compare the method with som...
Article
Full-text available
Various approaches have been developed for quantifying and displaying network traffic information for determining network status and in detecting anomalies. Although many of these methods are effective, they rely on the collection of long-term network statistics. Here, we present an approach that uses short-term observations of network features and...
Article
This paper describes a new method developed for fusion of X-ray and fluorescent molecular tomography (FMT) images. For easier diagnostics, images obtained from X-ray and FMT sources are fused to generate perceptibly informative image display using the spatial and spectral domain properties of the images. The basic premise in this research originate...
Article
Full-text available
This paper describes a method developed to assist in the detection and reconstruction of a three dimensional (3D) model of the human upper airway using cone beam computed tomography (CBCT) image slices and a 3D Gaussian smoothing kernel. The segmented and reconstructed volumetric airway is characterized by the corresponding three principal axes tha...
Conference Paper
In this work, we develop a fast binary partition tree based variable size video coding system. New adaptive algorithms proposed herein are applied to a video encoder with binary partition trees. First, to reduce the computation for block-matching, an adaptive search area method is described which adjusts the searching region according to the size o...
Article
A novel spatio-temporal (ST) three dimensional (3D) adaptive filter bank has been proposed based on the optimization techniques. The proposed adaptive algorithm is defined to track the 3D broadband spatio-temporal plane wave signal. For designing such an adaptive 3D filter bank, the orientation of 3D broadband plane wave signal in frequency domain...
Conference Paper
This paper describes a method developed to assist in the detection and reconstruction of the human upper airway using cone beam computed tomography (CBCT) image slices and a three dimensional (3D) Gaussian kernel blurring filter. The segmented airway is characterized by the corresponding three principal axes that are selected for viewing direction...
Article
This paper introduces a drowsiness scale which illustrates instantaneous overall predictions about observed anomalous driver behavior. Driver can be informed about her/his own driving conditions by the camera mounted inside of the vehicle. Data obtained from driver behavior by observation is not sufficient to make a correct decision about overall v...
Conference Paper
Full-text available
This paper presents a time-varying Gabor filter bank predictor for use with vehicle tracking via surveillance video. A frame-based 2D Gabor-filter bank is selected as a primary detector for any changes in a given video frame sequence. Detected changes are localized in each frame by fitting a bounding box on the silhouette of the vehicle in the regi...
Conference Paper
Entropy has been widely used to quantify information for display and examination in determining network status and in detecting anomalies. Although entropy-based methods are effective, they rely on long-term network statistics. Here, we propose an approach that deduces short term observations of network features and their respective time averaged e...
Conference Paper
Full-text available
Fast and efficient detection of anomalies is essential for maintaining a robust and secure network. This research presents a method of anomaly detection based on adaptive Wiener filtering of noise followed by ARMA modeling of network flow data. We dynamically calculate noise and traffic signal statistics using network-monitoring metrics for traffic...
Conference Paper
In this paper, a new block-based motion estimation (ME) method is proposed which uses the Kalman filtering (KF) with adaptive block partitioning (ABP) to improve the motion estimates resulting from conventional block-matching algorithms (BMAs). In our method, a first order autoregressive model is applied to the motion vectors (MVs) obtained by BMAs...
Conference Paper
Three dimensional (3D) shape adaptive cone filter banks are ideally required for selectively filtering of sampled broad band 3D plane wave signals on the basis of their energy distribution. In the proposed design, the shape of each band of the conventional 3D cone filter bank has been adapted based on the energy distribution of the spatio-temporal...
Conference Paper
In this work, a new block-based motion estimation method using the adaptive Kalman filtering (KF) based on one-dimensional (1-D) and two-dimensional (2-D) autoregressive (AR) models is proposed to improve the motion estimates. Conventional block-matching algorithms (BMAs) are utilized to obtain the measured motion vectors (MVs). Autoregressive mode...
Conference Paper
This paper presents a new adaptive Kalman filtering method to improve the performance of block-based motion estimation. In our work, measured motion vectors are obtained by a conventional block-matching algorithm (BMA). A first order autoregressive model is employed to fit the motion correlation between neighboring blocks and then to achieve the pr...
Conference Paper
An efficient block-matching (BM) method is proposed in this paper, which is a hybrid of full search (FS) and fast search block-matching algorithms (BMAs). The block-matching process is carried out in two stages. In the first stage, initial block-matching is applied to a few selected blocks in the frame using FS. To reduce computation, the search wi...
Article
Hyperspectral imagery (HSI) is a relatively new technology capable of relaying intensity information gathered from both visible and non-visible ranges of the electromagnetic spectrum. HSI images can contain hundreds of bands, which present a problem when an image analyst must select the most relevant bands from such an image for visualization, part...
Conference Paper
Full-text available
The appeal of change detection methods for surveillance systems arises from the need to monitor perturbations in the sensor’s field of view. Applications of change detection include satellite imagery, digital video compression algorithms, medical diagnosis, damage monitoring, and object tracking. The algorithm developed in this study is capable of...
Conference Paper
Full-text available
This paper builds upon our earlier work by applying an optimized version of our non-linear scene prediction method to traffic surveillance video. As previously, a Gabor-filter bank has been selected as a primary detector for any changes in a given image sequence. The detected ROI (region of interest) in arbitrary motion is fed to a non-linear Kalma...
Article
Hu and Zernike moments have been widely used in many shape recognition and object classification tasks. The Hu moments are the projections of an image I(x,y) on the basis functions formed by the monomials xPyq of non-orthogonal nature. Zernike moments are computed based on a set of orthogonal polynomials over the interior of the unit circle x²+y²<E...
Conference Paper
Full-text available
This paper describes a non-linear IR (infra-red) scene prediction method for range video surveillance and navigation. A Gabor-filter bank is selected as a primary detector for any changes in a given IR range image sequence. The detected ROI (region of interest) involving arbitrary motion is fed to a non-linear Kalman filter for predicting the next...
Article
Full-text available
In this paper, we present a method that detects lesions in two-dimensional (2D) cross-sectional brain images. By calculating the major and minor axes of the brain, we calculate an estimate of the background, without any a priori information, to use in inverse filtering. Shape saliency computed by a Gabor filter bank is used to further refine the re...
Conference Paper
In this paper, we present a new digital video watermarking technique using singular value decomposition (SVD) and two-dimensional principal component analysis (2DPCA). The SVD is used to utilized in the spatial domain while the 2DPCA is employed for embedding in the time domain. We demonstrate that the framework based on the combined use of SVD and...
Conference Paper
Detecting and recognizing objects in unstructured environments is one of the most challenging tasks in computer vision research. We propose an innovative algorithm, called deformable illumination, to address the problem of illumination variance in natural environments. Parallel to the role of deformable shape in object recognition, deformable illum...
Article
A new algorithm that can be used to automatically recognize and classify malignant lymphomas and leukemia is proposed in this paper. The algorithm utilizes the morphological watersheds to obtain boundaries of cells from cell images and isolate them from the surrounding background. The areas of cells are extracted from cell images after background s...
Article
This paper describes a method that overcomes the problem of internal deformations in three-dimensional (3D) range image identification. Internal deformations can be caused by several factors including stereo camera-pair misalignment, surface irregularities, active vision methods' incompatibilities, image imperfections, and changes in illumination s...
Conference Paper
Full-text available
In this paper, we present a method that detects lesions in two-dimensional (2D) cross-sectional brain images. Use of the morphological watershed segmentation technique localizes shape variation in the gray level distribution of brain images and, in turn, identifies the regions with abnormal shape and/or texture structure. The detected brain areas a...
Article
Content-based image retrieval is an important research topic in computer vision. We present a new method that combines region of interest (ROI) detection and relevance feedback. The ROI based approach is more accurate in describing the image content than using global features, and the relevance feedback makes the system to be adaptive to subjective...
Conference Paper
As one of the key techniques for futuristic man-machine interface, facial expression analysis has received much attention in recent years. This paper proposes a hierarchical approach to facial expression recognition in image sequences by exploiting both spatial and temporal characteristics within the framework of hierarchical hidden Markov models (...
Article
Spectral (color) and spatial (shape) features available in pictures are two significant sources of information for content-based retrieval of image databases. The developed adaptive shape transform approach originated from the premise that a two-dimensional (2-D) shape can be recovered from a set of Radon-transform-based projections. For search con...
Article
Modeling the three-dimensional (3D) microscopic cellular images analytically is rather a difficult task due to their random shapes and deformable characteristics. One remedy is to use the topographic structures to approximate the sample surfaces and produce the unknown molecular structures by means of deformable shape generation methods from the to...
Conference Paper
This paper presents work done based on second order statistical features including cross- and auto-correlations as well as co-occurrence matrices of iris images in an attempt to extract a simple, yet powerful, set of features of an iris as a biometric. Prior to our work, the most prevalent methods for iris identification include the frontier work b...