Geospatial assessment of pest-induced forest damage through the use of UAV-bases NIR imaging and Gi-technology

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Diagnostic agreement between panoramic radiographs and color doppler images of carotid atheroma

The aim of this study was to investigate the agreement between diagnoses of calcified atheroma seen on panoramic radiographs and color Doppler images. Our interest stems from the fact that panoramic images can show the presence of atheroma regardless of the level of obstruction detected by color Doppler images. Panoramic and color Doppler images of 16 patients obtained from the archives of the Health Department of the city of Valença, RJ, Brazil, were analyzed in this study. Both sides of each patient were observed on the images, with a total of 32 analyzed cervical regions. The level of agreement between diagnoses was analyzed using the Kappa statistics. There was a high level of agreement, with a Kappa value of 0.78. In conclusion, panoramic radiographs can help detecting calcifications in the cervical region of patients susceptible to vascular diseases predisposing to myocardial infarction and cerebrovascular accidents. If properly trained and informed, dentists can refer their patients to a physician for a cardiovascular evaluation in order to receive proper and timely medical treatment.

Hot tool temperature analysis though infrared images

Textile manufacture occupies a prominent place in the national economy. Because of its importance researches have been made on the development of new materials, equipment and methods used in the production process. The cutting of textiles starts in the basic stage, to be followed by the process of the making of clothes and other articles. In the hot cutting of fabric, one of the variables of great importance in the control of the process is the contact temperature between the tool and the fabric. This work presents a technique for the measurement of the temperature based on the processing of infrared images. With this purpose, it was developed a system which is composed of an infrared camera, a framegrabber PC board and a software which analyses the punctual temperature in the cut area enabling the operator to achieve the necessary control of other variables involved in the process.

Automated grading of left ventricular segmental wall motion by an artificial neural network using color kinesis images

The present study describes an auxiliary tool in the diagnosis of left ventricular (LV) segmental wall motion (WM) abnormalities based on color-coded echocardiographic WM images. An artificial neural network (ANN) was developed and validated for grading LV segmental WM using data from color kinesis (CK) images, a technique developed to display the timing and magnitude of global and regional WM in real time. We evaluated 21 normal subjects and 20 patients with LVWM abnormalities revealed by two-dimensional echocardiography. CK images were obtained in two sets of viewing planes. A method was developed to analyze CK images, providing quantitation of fractional area change in each of the 16 LV segments. Two experienced observers analyzed LVWM from two-dimensional images and scored them as: 1) normal, 2) mild hypokinesia, 3) moderate hypokinesia, 4) severe hypokinesia, 5) akinesia, and 6) dyskinesia. Based on expert analysis of 10 normal subjects and 10 patients, we trained a multilayer perceptron ANN using a back-propagation algorithm to provide automated grading of LVWM, and this ANN was then tested in the remaining subjects. Excellent concordance between expert and ANN analysis was shown by ROC curve analysis, with measured area under the curve of 0.975. An excellent correlation was also obtained for global LV segmental WM index by expert and ANN analysis (R² = 0.99). In conclusion, ANN showed high accuracy for automated semi-quantitative grading of WM based on CK images. This technique can be an important aid, improving diagnostic accuracy and reducing inter-observer variability in scoring segmental LVWM.

Automatic Optic Disc Boundary Extraction from Color Fundus Images

Efficient optic disc segmentation is an important task in automated retinal screening. For the same reason optic disc detection is fundamental for medical references and is important for the retinal image analysis application. The most difficult problem of optic disc extraction is to locate the region of interest. Moreover it is a time consuming task. This paper tries to overcome this barrier by presenting an automated method for optic disc boundary extraction using Fuzzy C Means combined with thresholding. The discs determined by the new method agree relatively well with those determined by the experts. The present method has been validated on a data set of 110 colour fundus images from DRION database, and has obtained promising results. The performance of the system is evaluated using the difference in horizontal and vertical diameters of the obtained disc boundary and that of the ground truth obtained from two expert ophthalmologists. For the 25 test images selected from the 110 colour fundus images, the Pearson correlation of the ground truth diameters with the detected diameters by the new method are 0.946 and 0.958 and, 0.94 and 0.974 respectively. From the scatter plot, it is shown that the ground truth and detected diameters have a high positive correlation. This computerized analysis of optic disc is very useful for the diagnosis of retinal diseases

Retrieving Cloud Characteristics from Ground-Based Daytime Color All-Sky Images

A discussion is presented of daytime sky imaging and techniques that may be applied to the analysis of full-color sky images to infer cloud macrophysical properties. Descriptions of two different types of skyimaging systems developed by the authors are presented, one of which has been developed into a commercially available instrument. Retrievals of fractional sky cover from automated processing methods are compared to human retrievals, both from direct observations and visual analyses of sky images. Although some uncertainty exists in fractional sky cover retrievals from sky images, this uncertainty is no greater than that attached to human observations for the commercially available sky-imager retrievals. Thus, the application of automatic digital image processing techniques on sky images is a useful method to complement, or even replace, traditional human observations of sky cover and, potentially, cloud type. Additionally, the possibilities for inferring other cloud parameters such as cloud brokenness and solar obstruction further enhance the usefulness of sky imagers

Detecção e seguimento de objectos em imagens termográficas: análise experimental de modelos de descrição

A instalação de sistemas de videovigilância, no interior ou exterior, em locais como aeroportos, centros comerciais, escritórios, edifícios estatais, bases militares ou casas privadas tem o intuito de auxiliar na tarefa de monitorização do local contra eventuais intrusos. Com estes sistemas é possível realizar a detecção e o seguimento das pessoas que se encontram no ambiente local, tornando a monitorização mais eficiente. Neste contexto, as imagens típicas (imagem natural e imagem infravermelha) são utilizadas para extrair informação dos objectos detectados e que irão ser seguidos. Contudo, as imagens convencionais são afectadas por condições ambientais adversas como o nível de luminosidade existente no local (luzes muito fortes ou escuridão total), a presença de chuva, de nevoeiro ou de fumo que dificultam a tarefa de monitorização das pessoas. Deste modo, tornou‐se necessário realizar estudos e apresentar soluções que aumentem a eficácia dos sistemas de videovigilância quando sujeitos a condições ambientais adversas, ou seja, em ambientes não controlados, sendo uma das soluções a utilização de imagens termográficas nos sistemas de videovigilância. Neste documento são apresentadas algumas das características das câmaras e imagens termográficas, assim como uma caracterização de cenários de vigilância. Em seguida, são apresentados resultados provenientes de um algoritmo que permite realizar a segmentação de pessoas utilizando imagens termográficas. O maior foco desta dissertação foi na análise dos modelos de descrição (Histograma de Cor, HOG, SIFT, SURF) para determinar o desempenho dos modelos em três casos: distinguir entre uma pessoa e um carro; distinguir entre duas pessoas distintas e determinar que é a mesma pessoa ao longo de uma sequência. De uma forma sucinta pretendeu‐se, com este estudo, contribuir para uma melhoria dos algoritmos de detecção e seguimento de objectos em sequências de vídeo de imagens termográficas. No final, através de uma análise dos resultados provenientes dos modelos de descrição, serão retiradas conclusões que servirão de indicação sobre qual o modelo que melhor permite discriminar entre objectos nas imagens termográficas.

Weed mapping using a machine vision system

Weed mapping is a useful tool for site-specific herbicide applications. The objectives of this study were (1) to determine the percentage of land area covered by weeds in no-till and conventionally tilled fields of common bean using digital image processing and geostatistics, and (2) to compare two types of cameras. Two digital cameras (color and infrared) and a differential GPS were affixed to a center pivot structure for image acquisition. Sample field images were acquired in a regular grid pattern, and the images were processed to estimate the percentage of weed cover. After calculating the georeferenced weed percentage values, maps were constructed using geostatistical techniques. Based on the results, color images are recommended for mapping the percentage of weed cover in no-till systems, while infrared images are recommended for weed mapping in conventional tillage systems.

Spatial and radiometric fidelity of airborne multispectral imagery in the context of land-cover change analyses

The goal was to quantitatively estimate and compare the fidelity of images acquired with a digital imaging system (ADAR 5500) and generated through scanning of color infrared aerial photographs (SCIRAP) using image-based metrics. Images were collected nearly simultaneously in two repetitive flights to generate multi-temporal datasets. Spatial fidelity of ADAR was lower than that of SCIRAP images. Radiometric noise was higher for SCIRAP than for ADAR images, even though noise from misregistration effects was lower. These results suggest that with careful control of film scanning, the overall fidelity of SCIRAP imagery can be comparable to that of digital multispectral camera data. Therefore, SCIRAP images can likely be used in conjunction with digital metric camera imagery in long-term landcover change analyses.

Improving face recognition with multispectral fusion and support vector machines

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Infrared thermography to quantify the risk of breast cancer.

From the last decades, infrared thermography is quite often associated with things other than clinical medicine. For example, the chemical, automobile, aeronautic industries and civil engineering. However, thermography is where infrared images of the breast are analyzed by board certified thermographers and an abnormal thermogram is reported as the significant risk for the existence of breast tumor (Ng, 2009). Thermography is a painless, noninvasive, no radiation, as well as being cheaper and faster, easier access. The aim of this review was to identify the views of clinicians on the use of thermography for quantifying the risk of breast cancer. We used articles published recently in a reliable database. Thermography has been convicted over the years; it has been labeled by subjective interpretation. Most of the reviewed articles agree that mammography is currently the main examination chosen by doctors for the screening of breast cancer (Acharya et al., 2010; Kennedy et al., 2009). However, several studies have reported promising results for the technique (Wang et al., 2010). Additionally, some authors suggest that thermography is complementary to other diagnostic methods, and that the best strategy for the early detection of breast cancer would be to use them together (Kennedy et al., 2009; Hersh, 2004). The combination of thermal imaging with other tests would increase accuracy, sensitivity and specificity of the evaluation and allow a better quantification of the risk of breast cancer.

Systematic Monitoring of Wound Healing Using a Hand-held Near-Infrared Optical Scanner

According to the American Podiatric Medical Association, about 15 percent of the patients with diabetes would develop a diabetic foot ulcer. Furthermore, foot ulcerations leads to 85 percent of the diabetes-related amputations. Foot ulcers are caused due to a combination of factors, such as lack of feeling in the foot, poor circulation, foot deformities and the duration of the diabetes. To date, the wounds are inspected visually to monitor the wound healing, without any objective imaging approach to look before the wound’s surface. Herein, a non-contact, portable handheld optical device was developed at the Optical Imaging Laboratory as an objective approach to monitor wound healing in foot ulcer. This near-infrared optical technology is non-radiative, safe and fast in imaging large wounds on patients. The FIU IRB-approved study will involve subjects that have been diagnosed with diabetes by a physician and who have developed foot ulcers. Currently, in-vivo imaging studies are carried out every week on diabetic patients with foot ulcers at two clinical sites in Miami. Near-infrared images of the wound are captured on subjects every week and the data is processed using customdeveloped Matlab-based image processing tools. The optical contrast of the wound to its peripheries and the wound size are analyzed and compared from the NIR and white light images during the weekly systematic imaging of wound healing.

Three-dimensional finite element thermal analysis of dental tissues irradiated with Er,Cr:YSGG laser

In the present study, a finite element model of a half-sectioned molar tooth was developed in order to understand the thermal behavior of dental hard tissues (both enamel and dentin) under laser irradiation. The model was validated by comparing it with an in vitro experiment where a sound molar tooth was irradiated by an Er,Cr:YSGG pulsed laser. The numerical tooth model was conceived to simulate the in vitro experiment, reproducing the dimensions and physical conditions of the typical molar sound tooth, considering laser energy absorption and calculating the heat transfer through the dental tissues in three dimensions. The numerical assay considered the same three laser energy densities at the same wavelength (2.79 mu m) used in the experiment. A thermographic camera was used to perform the in vitro experiment, in which an Er, Cr: YSGG laser (2.79 mu m) was used to irradiate tooth samples and the infrared images obtained were stored and analyzed. The temperature increments in both the finite element model and the in vitro experiment were compared. The distribution of temperature inside the tooth versus time plotted for two critical points showed a relatively good agreement between the results of the experiment and model. The three dimensional model allows one to understand how the heat propagates through the dentin and enamel and to relate the amount of energy applied, width of the laser pulses, and temperature inside the tooth. (C) 2008 American Institute of Physics. [DOI: 10.1063/1.2953526]