Mehrube Mehrubeoglu

Measurement and calculation of the two-dimensional backscattering Mueller matrix of a turbid medium

We present both experimental and Monte Carlo-based simulation results for the diffusely backscattered intensity patterns that arise from illumination of a turbid medium with a polarized laser beam. A numerical method that allows the calculation of all 16 elements of the two-dimensional Muller matrix is used; moreover, it is shown that only seven matrix elements are independent. To validate our method, we compared our simulations with experimental measurements, using a turbid medium consisting of 2.02-microm -diameter polystyrene spheres suspended in deionized water. By varying the incident polarization and the analyzer optics for the experimental measurements, we obtained the diffuse backscattering Mueller matrix elements. The experimental and the numerical results are in good agreement.

Skin lesion classification using oblique-incidence diffuse reflectance spectroscopic imaging

We discuss the use of a noninvasive in vivo optical technique, diffuse reflectance spectroscopic imaging with oblique incidence, to distinguish between benign and cancer-prone skin lesions. Various image features were examined to classify the images from lesions into benign and cancerous categories. Two groups of lesions were processed separately: Group 1 includes keratoses, warts versus carcinomas; and group 2 includes common nevi versus dysplastic nevi. A region search algorithm was developed to extract both one- and two-dimensional spectral information. A bootstrap-based Bayes classifier was used for classification. A computer-assisted tool was then devised to act as an electronic second opinion to the dermatologist. Our approach generated only one false-positive misclassification out of 23 cases collected for group 1 and two misclassifications out of 34 cases collected for group 2 under the worst estimation condition.

A Survey of Green Energy Technology and Policy

With many current scientific studies pointing to global warming and climate changes caused by greenhouse gases, there is an ever increasing societal push for renewable environmentally friendly green technologies to help reduce greenhouse gas emissions resulting from fossil fuel consumption. Government policy plays a key role in the development and wide-scale implementation of green technology. Many research and industry groups are pursuing research in alternative green energy sources and production. A survey of renewable and green technologies is conducted in this paper; from this survey, it is apparent that much more research, education, and continued support are needed to further promote and improve existing and new renewable technologies to meet the goals and emission standards set by international agreements and governments.

Effect of molecular concentrations in tissue-simulating phantoms on images obtained using diffuse reflectance polarimetry

We have investigated the possibility of using diffuse reflectance polarimetry to detect changes caused by different molecular compounds and concentrations in tissue-simulating phantoms. The effects of glucose, B-alanine and l-lysine at different concentrations in turbid media have been investigated separately. This approach is based on the effect of optical properties on the polarization state of light. The results show that this method has potential for determining changes in molecular concentrations in highly scattering biological media from polarization images.

Real-time eye tracking using a smart camera

Real-time eye and iris tracking is important for handsoff gaze-based password entry, instrument control by paraplegic patients, Internet user studies, as well as homeland security applications. In this project, a smart camera, LabVIEW and vision software tools are utilized to generate eye detection and tracking algorithms. The algorithms are uploaded to the smart camera for on-board image processing. Eye detection refers to finding eye features in a single frame. Eye tracking is achieved by detecting the same eye features across multiple image frames and correlating them to a particular eye. The algorithms are tested for eye detection and tracking under different conditions including different angles of the face, head motion speed, and eye occlusions to determine their usability for the proposed applications. This paper presents the implemented algorithms and performance results of these algorithms on the smart camera.

Resolving Mixed Algal Species in Hyperspectral Images

We investigated a lab-based hyperspectral imaging systems response from pure (single) and mixed (two) algal cultures containing known algae types and volumetric combinations to characterize the systems performance. The spectral response to volumetric changes in single and combinations of algal mixtures with known ratios were tested. Constrained linear spectral unmixing was applied to extract the algal content of the mixtures based on abundances that produced the lowest root mean square error. Percent prediction error was computed as the difference between actual percent volumetric content and abundances at minimum RMS error. Best prediction errors were computed as 0.4%, 0.4% and 6.3% for the mixed spectra from three independent experiments. The worst prediction errors were found as 5.6%, 5.4% and 13.4% for the same order of experiments. Additionally, Beer-Lamberts law was utilized to relate transmittance to different volumes of pure algal suspensions demonstrating linear logarithmic trends for optical property measurements.

Characterization of skin lesion texture in diffuse reflectance spectroscopic images

This paper examines various texture features extracted from skin lesion images obtained by using diffuse reflectance spectroscopic imaging. Different image texture features have been applied to such images to separate precancerous from benign cases. These features are extracted based on the co-occurrence matrix, wavelet decomposition , fractal signature, and granulometric approaches. The results so far indicate that fractal and wavelet-based features are effective in distinguishing precancerous from benign cases.

Hyperspectral imaging and analysis of mixed algae species in liquid media

In this paper, a laboratory-based hyperspectral imaging system is used to acquire hyperspectral data cubes from different algae samples of known mixtures. The data are obtained under controlled and repeatable conditions. Hyperspectral image processing is complicated by the size of the corresponding datasets so hyperspectral image pre-processing techniques such as dimensionality reduction are necessary before spectral analysis. We assessed hyperspectral response of mixed algal cultures containing two algae types to characterize the laboratory-based hyperspectral imaging system. Changes in the hyper spectral imaging systems response to variations in volume and combinations of algae concentrations were tested. Preliminary results demonstrate the systems capability to differentiate algal species, concentrations and sample volumes.

Determination of traffic intensity from camera images using image processing and pattern recognition techniques

The goal of this project was to detect the intensity of traffic on a road at different times of the day during daytime. Although the work presented utilized images from a section of a highway, the results of this project are intended for making decisions on the type of intervention necessary on any given road at different times for traffic control, such as installation of traffic signals, duration of red, green and yellow lights at intersections, and assignment of traffic control officers near school zones or other relevant locations. In this project, directional patterns are used to detect and count the number of cars in traffic images over a fixed area of the road to determine local traffic intensity. Directional patterns are chosen because they are simple and common to almost all moving vehicles. Perspective vision effects specific to each camera orientation has to be considered, as they affect the size and direction of patterns to be recognized. In this work, a simple and fast algorithm has been developed based on horizontal directional pattern matching and perspective vision adjustment. The results of the algorithm under various conditions are presented and compared in this paper. Using the developed algorithm, the traffic intensity can accurately be determined on clear days with average sized cars. The accuracy is reduced on rainy days when the camera lens contains raindrops, when there are very long vehicles, such as trucks or tankers, in the view, and when there is very low light around dusk or dawn.

Differentiation of bacterial colonies and temporal growth patterns using hyperspectral imaging

Detection and identification of bacteria are important for health and safety. Hyperspectral imaging offers the potential to capture unique spectral patterns and spatial information from bacteria which can then be used to detect and differentiate bacterial species. Here, hyperspectral imaging has been used to characterize different bacterial colonies and investigate their growth over time. Six bacterial species (Pseudomonas fluorescens, Escherichia coli, Serratia marcescens, Salmonella enterica, Staphylococcus aureus, Enterobacter aerogenes) were grown on tryptic soy agar plates. Hyperspectral data were acquired immediately after, 24 hours after, and 96 hours after incubation. Spectral signatures from bacterial colonies demonstrated repeatable measurements for five out of six species. Spatial variations as well as changes in spectral signatures were observed across temporal measurements within and among species at multiple wavelengths due to strengthening or weakening reflectance signals from growing bacterial colonies based on their pigmentation. Between-class differences and within-class similarities were the most prominent in hyperspectral data collected 96 hours after incubation.