Due to the problems of targets submerged to the background, which could easily produce ghosts, and hard complete extraction of dim targets in the surveillance video, we propose the moving target extraction and fast vi...
详细信息
Due to the problems of targets submerged to the background, which could easily produce ghosts, and hard complete extraction of dim targets in the surveillance video, we propose the moving target extraction and fast video reconstruction algorithm in accord with visual principle. The sample selection strategy of VIBE algorithm is improved to alleviate the errors of pixel classification. The infrared imaging features are fused to suppress the artifact. A regional growth mechanism is established to extract and store moving targets and pure background regions, and according to the characteristics of video surveillance, it is the first to establish the mapping mechanism of target, background and video to propose the fast video reconstruction algorithm. The experiment shows that the algorithm can extract the moving target completely, establish the pure background in a variety of complex conditions, and greatly reduce the storage room of the surveillance video.
The United States Environmental Protection Agency Airborne Spectral Photometric Environmental Collection technology (ASPECT) program uses airborne remote sensing to support first responders in responding to incidents ...
The United States Environmental Protection Agency Airborne Spectral Photometric Environmental Collection technology (ASPECT) program uses airborne remote sensing to support first responders in responding to incidents in which chemical or radiological materials are released into the environment. Two main tasks of the ASPECT program are the detection of chemical plumes in the atmosphere in accidental chemical releases and the detection of marine oil slicks on seawater in oil spill accidents. detections are made in near real time by applying software-based mathematical classification models (classifiers) to the imagery data collected by a downward looking infrared (IR) multispectral sensor on the aircraft. The classifiers classify each image pixel as "plume" or "non-plume" or "oil" or "non-oil", depending on the application. The research described in this dissertation focuses on the development of classifiers for future use in the above-mentioned emergency response applications.; Three classifiers have been developed for chemical plume detection. Methanol was used as the target compound to demonstrate the methodologies for the development of the classifiers. In the development of the first plume classifier, training data were collected from controlled methanol release field experiments that mimicked an accidental chemical release at an industrial facility. The classifier was built using multi-layer shallow neural networks (MSNN) on a set of optimized ratios of band intensities obtained from a series of feature extraction procedures applied to the IR radiance data.; The limitation of the first plume classifier was that it required time-consuming and expensive field experiments to obtain the analyte-active training data, which motivated the development of the second plume classifier. The second plume classifier utilized a simulation methodology to compute the plume radiances that comprised the analyte-active training data. This methodology used Planck's radiation law and
The advantages of using far-infraredtechnology in guiding systems, warning systems or surveillance systems have been demonstrated in defense applications through a large span of imaging functions such as detection, t...
详细信息
ISBN:
(纸本)9781510626706
The advantages of using far-infraredtechnology in guiding systems, warning systems or surveillance systems have been demonstrated in defense applications through a large span of imaging functions such as detection, target recognition and positive identification in complex environments. Used as a complementary tool in a set of camera sensing technologies, the far-infrared thermal camera provides the key sense to improve system performance and increase human classification robustness. This enhanced capability relies on the detection of the unique thermal signature of a pedestrian in any weather and light conditions, day or night, without being glared by the sun or any light source. Implementing vision system based on shutterless far-infrared solution into an autonomous detection system can reduce the rate of false positive detection. Being an imaging technology, far-infrared camera using ULIS technology can be easily integrated into standard platform while minimizing computation resources required by detection algorithms thanks to the thermal signature detection.
This paper proposes a method for detecting oil tank targets that combines improved blotch feature detection and SVM sample learning in order to address deficiencies in the recognition of oil tank targets in thermal in...
详细信息
ISBN:
(数字)9781510627130
ISBN:
(纸本)9781510627130
This paper proposes a method for detecting oil tank targets that combines improved blotch feature detection and SVM sample learning in order to address deficiencies in the recognition of oil tank targets in thermal infrared remote sensing images due to indistinct edge information, high noise level, and small dimensions. First of all, initial detection was conducted on the basis of blotch features and mass features. Then the features of oil tank targets and an optimal combination of classification features were generated from sample learning. Finally oil tank targets were detected through classification based on SVM sample learning. The results of the experiment show that: 1) by setting appropriate parameters, this method combines blotch features and textural features for the extraction of a more comprehensive range of TIR oil tank features that can achieve the effective detection of oil tank targets;2) based on the detection of blotch targets, this method can filter out false targets with relatively high accuracy and is capable of more stable and efficient recognition of Type #1 and Type #2 targets.
External atmospheric infrared (IR) target recognition is an important research topic of space surveillance systems. The different micromotion states of the target result in respective features in the obtained sequence...
详细信息
暂无评论