Optical Analysis of Solar Concentrators Using Photogrammetry Process

As the optical efficiency of solar concentrators has a high impact on its thermal performance. However a qualification method determining the geometrical accuracy of a solar concentrator system is necessary. The purpose of this chapter is to gives an optical analysis of solar concentrator with an imaging process in order to improve the thermal efficiency of the solar concentrator. In this order measurement techniques used to determine geometric errors of the solar concentrating system have been described. Intercept factor, slope error and displacement error have been identified and analyzed. Examples of the intercept factor for concentrator reflector along with optical efficiency has been developed and determined related to the experimental results given by photogrammetry measurement technique.

Computational Intelligence Foundations and Principles

AI has been defined in different ways, including the abilities for abstract thought, understanding, communication, reasoning, learning, retaining, planning, and solving. Intelligence is most widely studied in humans, but has also been observed in animals and plants. AI is the intelligence of machines or the simulation of intelligence in machines. AI is both the intelligence of machines and the branch of Computer Science which aims to create it, through the study and design of intelligent agents or rational agents, where an intelligent agent is a system that perceives its environment and takes actions which maximize its chances of success. Achievements include constrained and well-defined problems such as games, crossword-solving and optical character recognition. Among the traits that researchers hope machines will exhibit are reasoning, knowledge, planning, learning, communication, perception, and the ability to move and manipulate objects. In the field of AI there is no consensus on how closely the brain should be simulated.

Thermal Imaging in Medical Science

Thermal imaging is a non-destructive, non-contact and rapid system. It reports temperature through measuring infrared radiation emanated by an object/ material surface. Automated thermal imaging system involves thermal camera equipped with infrared detectors, signal processing unit and image acquisition system supported by computer. It is elaborated in wide domains applications. Extensive focus is directed to the thermal imaging in the medical domain especially breast cancer detection. This chapter provided the main concept and the different applications of thermal imaging. It explores and analyses several works in the light of studding the thermograph. It is an effective screening tool for breast cancer prediction. Studies justify that thermography can be considered a complementary tool to detect breast diseases. The current chapter reviews many usages and limitations of thermography in biomedical field. Extensive recommendations for future directions are summarized to provide a structured vision of breast thermography.

An Intelligent Thermal Imaging System Adopting Fuzzy-Logic-Based Viola Jones Method in Flu Detection

Some infectious diseases can spread rapidly via a community of human or animals or both, either through airborne particles or viruses. Such rapid spread diseases may become a local, national or international widespread and contagious threat. As a symptom of infection, the body temperature of a disease carrier is higher than normal people. In this chapter, flu detection system using thermal imaging tool and computer vision techniques are discussed. An automatic flu detection method adopting human object extraction algorithm and fuzzy logic based Viola Jones algorithm are also discussed. The proposed system able to capture a thermogram of the human subject, detecting the eye region of the human subject, calculating the pixels values around the detected eye region, converted to temperature readings and further classified the subject's body temperature whether the subject satisfies a flu condition or not. Experimental results also shown that the proposed fuzzy logic based Viola Jones algorithm can trace out flu infectious personal from the input thermal images up to 80% of accuracy.

Human Health Diagnosis System Based on Iris Features

Iris feature has been used in authentication systems in many real time applications and is proved to provide high accuracy. Apart from authentication iris features can also be used for detecting pathological changes in human body and diagnose human health. The present study analyses the relationship between human iris anatomy and their health, as it is proved that changes in human health condition reflects the iris. Basically, in authentication system iris texture features are used for identification, in the proposed work iris texture and geometric features can also be deployed in diagnosing human health. The texture features present in the human iris are extracted using the mathematical statistical measure which is used to specify the characteristics of the texture of an image using gray-level co-occurrence matrix. The iris and pupil are extracted and correlated to the compactness features of the circle. Based on the comparison the system enables in prediction of abnormalities in the iris texture and identifies the affected person.

The Brain Tumor Segmentation Using Fuzzy C-Means Technique

Image segmentation is a technique which divides an image into its constituent regions or objects. Segmentation continues till we reach our area of interest or the specified object of target. This field offers vast future scope and challenges for the researchers. This proposal uses the fuzzy c mean technique to segment the different MRI brain tumor images. This proposal also shows the comparative results of Thresholding, K-means clustering and Fuzzy c- means clustering. Dice coefficient and Jaccards measure is used for accuracy of the segmentation in this proposal. Experimental results demonstrate the performance of the designed method.

Personal Authentication through Finger Knuckle Geometric and Texture Feature Measurements

Finger Knuckle biometric is an emerging automated human identification approach that has received extensive significance in the area of research and real time applications in the recent past. Generally, a typical finger knuckle biometric system investigates the finger knuckle patterns present in the outer bend surface of the finger back region i.e., proximal phalanx region. In contrast, this paper focuses on the entire finger back region which includes proximal and distal phalanx of the finger knuckle surface for recognition. Further, this paper investigates a novel approach to achieve improved performance by simultaneous extraction and integration of finger knuckle geometric and texture features from a captured finger knuckle region. The geometric measures are derived by means of angular geometric analysis method which extracts angular-based feature information for unique identification. Similarly, texture measures are derived through statistical-based texture analysis methods.

New Advances in Multidimensional Processing for Thermal Image Quality Enhancement

This chapter presents three recent methodologies about multidimensional processing for signal to noise ratio (SNR) and thermal contrast enhancement on sequences of thermographic images, acquired from active pulsed thermography experiments over composite slabs, mainly, carbon fiber reinforced plastic (CFRP). The first technique corresponds to noise pre-processing by means of iterative 3D filtering to take advantage of the high space-time correlation in thermal sequences; the other two techniques correspond to thermal contrast enhancement processing: one of them using an atypical median filtering scheme, and the other based on heat propagation discrete models. Beginning with their heuristic and mathematical foundations, and following with the algorithmic procedures development, advantages and limitations will be shown through suitable indexes for evaluation, and some comparisons with other similar techniques.

Thermal Imaging in Smart Applications

Temperature measurement is an essential requirement for a large number of smart applications in medicine, agriculture, environment, and security domains, to name but a few. Conventionally, temperature measurements are mostly performed using thermometers, thermocouples, thermistors, and resistance temperature detectors. Most of these instruments require physical contact with the object to measure temperature at specific points. Infrared thermography has revolutionized the concept of temperature measurement. Infrared thermal imaging (IRTI) can provide the temperature mapping without a physical contact with the object of interest from a reasonable distance. A typical IRTI system comprises of a thermal camera equipped with infrared detector, a signal processing unit and an image acquisition system, usually in the form of an embedded system. Such cameras are utilized for applications like fault detection, irrigation management, motion detection, etc. This chapter briefly introduces use of thermal imaging in medicine, agriculture, environment, smart home/cities and security applications.