Browsing by Subject "Infrared detectors."

Now showing 1 - 5 of 5

Open Access
CUDA based implementation of flame detection algorithms in day and infrared camera videos
(2011) Hamzaçebi, Hasan
Automatic fire detection in videos is an important task but it is a challenging problem. Video based high performance fire detection algorithms are important for the detection of forest fires. The usage area of fire detection algorithms can further be extended to the places like state and heritage buildings, in which surveillance cameras are installed. In uncontrolled fires, early detection is crucial to extinguish the fire immediately. However, most of the current fire detection algorithms either suffer from high false alarm rates or low detection rates due to the optimization constraints for real-time performance. This problem is also aggravated by the high computational complexity in large areas, where multicamera surveillance is required. In this study, our aim is to speed up the existing color video fire detection algorithms by implementing in CUDA, which uses the parallel computational power of Graphics Processing Units (GPU). Our method does not only speed up the existing algorithms but it can also reduce the optimization constraints for real-time performance to increase detection probability without affecting false alarm rates. In addition, we have studied several methods that detect flames in infrared video and proposed an improvement for the algorithm to decrease the false alarm rate and increase the detection rate of the fire.
Open Access
Passivation of InSb infrared photodetectors
(2010) Yumrukçu, Samed
Infrared detectors have wide range applications in both military and civilian life. One of the most commonly used infrared detectors is InSb detectors. InSb detector technology has been developing since 1950s. Fabricating p-n diodes to detect infrared radiation is a common way of constructing InSb detectors. Due to high free carrier concentration at room temperature, InSb detectors need to be cooled down to operate properly and usually liquid nitrogen is preferred for cooling. However, even at 77 K, tunneling and generation-recombination and surface leakage are not negligible and these effects result in dark current. Improving the photo current-to-dark current ratio is the main goal in design and fabrication of InSb photo detectors. One way of decreasing the dark current is passivating the exposed edges of the detector to reduce surface leakage current. Passivating the edges can result in decreasing in the surface leakage by eliminating the surface states (dangling bonds). Dielectric thin films like SiO2 and SiNx are commonly used for passivation. In this work, different sized detectors are fabricated and characterized by measuring I-V curves and spectral response. Different approaches are tested for passivation and a detailed comparison between detectors with different treatments is presented.
Open Access
Plasmonically enhanced silicon infrared Schottky detector
(2011) Polat, Kazım Gürkan
Open Access
Pyroelectric infrared (PIR) sensor based event detection
(2009) Soyer, Emin Birey
Pyroelectric Infra-red (PIR) sensors have been extensively used in indoor and outdoor applications as they are low cost, easy to use and widely available. PIR sensors respond to IR radiating objects moving in its viewing range. The current sensors give an output of logical one when they detect a hot object’s motion and a logical zero when there is no moving hot object. In this method, only moving objects can be detected and the rate of false alarm is high. New types of PIR sensors are more sophisticated and more capable. They have a lower false alarm ratio compared to classical ones. Although they can distinguish pets and humans, again they can only be used for detection of hot object motions due to the limitations caused by the usage of the simple comparator structure inside. This structure is unalterable, not flexible for development, and not suitable for implementing algorithms. A new approach is developed to use PIR sensors by modifying the sensor circuitry. Instead of directly using the output of a classical PIR sensor, an analog signal is extracted from the PIR output and it is sampled. As a result, intelligent signal processing algorithms can be developed using the discrete-time sensor signal. In this way, it is possible to develop human, pet and flame detection methods. It is also possible to find the direction of moving objects and estimate their distances from the sensor. Furthermore, the path of a moving target can be estimated using a PIR sensor array. We focus on object and event classification using sampled PIR sensor signals. Pet, human and flame detection methods are comparatively investigated. Different human motion events are modeled and classifed using Hidden Markov Models (HMM) and Conditional Gaussian Mixture Models (CGMMs). The sampled data is wavelet transformed for feature extraction and then fed into HMMs for analysis. The final decision is reached according to the Markov Model producing the highest probability. Experimental results demonstrate the reliability of the proposed HMM based decision and event classification algorithm.
Open Access
Volatile organic compounds (VOC) gas leak detection by using infrared sensors
(2009) Erden, Fatih
Advances in technology and industry leads to a rise in the living standards of people. However, this has also introduced a variety of serious problems, such as the undesired release of combustible and toxic gases which have become an essential part of domestic and industrial life. Therefore, detection and monitoring of VOC gases have become a major problem in recent years. In this thesis, we propose novel methods for detection and monitoring VOC gas leaks by using a Pyro-electric (or Passive) Infrared (PIR) sensor and a thermopile sensor. A continuous time analog signal is obtained for both of the sensors and sent to a PC for signal processing. While using the PIR sensor, we have Hidden Markov Models (HMM) for each type of event to be classified. Then, by using a probabilistic approach we determine which class any test signal belongs to. In the case of a thermopile sensor, in addition to Hidden Markov Modeling method, we also use a method based on the period of the sensor signal. The frequency of the output signal of the thermopile sensor increases with the presence of VOC gas leak. By using this fact, we control whether the period of a test signal is below a predefined threshold or not. If it is, our system triggers an alarm. Moreover, we present different methods to find the periods of a given signal.