Browsing by Subject "Infrared imaging"
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Item Infrared detection in Melanophila acuminata(2001-05) Hammer, Daniel Xavier; Welch, Ashley J., 1933-Item Segmentation of infrared images(Texas Tech University, 2002-05) Dhungana, AnujIn this thesis, we study some segmentation methods for infrared images. First we summarize the characteristics of infrared images and survey different approaches of segmentation. Our objective is to develop an image segmentation method for surveillance images, which helps isolate all major objects in the image. We study fuzzy logic based segmentation for this purpose. Our study shows that use of a suitable thresholding method is important prior to use of the fuzzy logic based method for refinement of boundaries of objects of interest. The existing fuzzy logic based method requires prior knowledge of the size of the target objects. We remove this requirement by using adaptive global thresholding heuristic based on image histogram. Next we extend this segmentation method for object matching between frames of surveillance image sequence and for object tracking.Item Sleeping in a society : social aspects of sleep within colonies of honey bees (Apis mellifera)(2010-05) Klein, Barrett Anthony; Gilbert, Lawrence E.; Mueller, Ulrich G.; Seeley, Thomas D.; Ryan, Michael J.; Abbott, John C.Sleep is a behavioral condition fraught with mystery. Its definition—either a suite of diagnostic behavioral characters, electrophysiological signatures, or a combination of the two—varies in the literature and lacks an over-arching purpose. In spite of these vagaries, sleep supports a large and dynamic research community studying the mechanisms, ontogeny, possible functions and, to a lesser degree, its evolution across vertebrates and in a small number of invertebrates. Sleep has been described and examined in many social organisms, including eusocial honey bees (Apis mellifera), but the role of sleep within societies has rarely been addressed in non-human animals. I investigated uniquely social aspects of sleep within honey bees by asking basic questions relating to who sleeps, when and where individuals sleep, the flexibility of sleep, and why sleep is important within colonies of insects. First, I investigated caste-dependent sleep patterns in honey bees and report that younger workers (cell cleaners and nurse bees) exhibit arrhythmic and brief sleep bouts primarily while inside comb cells, while older workers (food storers and foragers) display periodic, longer sleep bouts primarily outside of cells. Next, I mapped sleep using remote thermal sensing across colonies of honey bees after introducing newly eclosed workers to experimental colonies and following them through periods of their adult lives. Bees tended to sleep outside of cells closer to the edge of the hive than when asleep inside cells or awake, and exhibited caste-dependent thermal patterns, both temporally and spatially. Wishing to test the flexibility of sleep, I trained foragers to a feeder and made a food resource available early in the morning or late in the afternoon. The bees were forced to shift their foraging schedule, which consequently also shifted their sleep schedule. Finally, I sleep-deprived a subset of foragers within a colony by employing a magnetic “insominator” to test for changes in their signaling precision. Sleep-deprived foragers exhibited reduced precision when encoding direction information to food sources in their waggle dances. These studies reveal patterns and one possible purpose of sleep in the context of a society.Item Wavelet-based compression of infrared images using multiscale edges(Texas Tech University, 2003-05) Madan, Tarun KumarInfrared technology has found many exciting and useful applications in the fields ranging from surveillance to astronomy. Therefore the volume of IR data being collected is increasing rapidly. Thus, there is a strong interest in developing image encoding and compression algorithms, specifically for infrared images. Most compression schemes have been developed for photographic images, and very little study exists on IR image coding. These may not be optimized or even appropriate for Infrared data, because they do not take into consideration the peculiar characteristics of infrared images. For this purpose, we study a compression scheme based on edge detection and noise reduction within the wavelet framework. We begin by analyzing the effectiveness of wavelet based multi-scale edge scheme proposed by Mallat and Zhong [1] for compression and noise removal, and optimize it to suit the characteristics of infrared images.