An analysis based on the Jones matrix theoretical analysis is presented in this paper, which is based on the distributed optical fiber location system to study the polarization effect. A new improved distributed optical fiber structured is designed by using a Faraday rotation mirror ,the system is insensitive to the change of the polarization in the sensing part of the optical fiber, remove the linear birefringence and the orientation birefringence, the practicability of the system is increased.
Due to the light scattering and absorption, underwater images were blurred such as fog, uneven illumination, overexposure or lack of light. We proposed an image enhancement algorithm based on granular computing to enhance underwater optical image in this paper. First, the illumination information of underwater image was extracted. Then, we dividing the illumination information into granularity of different sizes from wide to thin by calculated the effectiveness indicators. Finally, by calculating their value and compensation for each granularity, we obtained the adaptive enhancement image. The simulation and experiment results verify the effectiveness of the algorithm.
A novel distributed fiber-optic sensor based on Wavelength Division Multiplex (WDM) for determining the position of disturbances is presented. The configuration and operating principle of the system is illustrated. The location principle and the method for the detection system are analyzed. Based on the initial method in the frequency domain, the system realizes the disturbances location using the WDM technology to compare the signals which are the same vibration corresponding to different light sources and light paths. Theory analysis and experiment results show that the proposed algorithm can realize the detection and location of the multipoint disturb signals rapidly and effectively, this method is simply and can be obtained easily, it could increase the length of fiber-optic sensors which has high measurement sensitivity and location precision.
In this paper, an edge extraction model based on artificial bee colony algorithm has been proposed to overcome the problems of concrete defect detection in complex underwater environment specialized to dam cracks detection. To enhance weak-object edge gray contrast under different brightness, the adaptive enhancement method is presented in which a concept of two-dimensional lateral inhibitory network is introduced and a border highlighting rule is designed. Furthermore, to increase the edge extraction effective, the improved artificial bee colony algorithm is used in which an optimization strategy is based on edge direction information. Some experiments are carried out on underwater dam crack images in different environments and the experimental results show the efficiency and effectiveness of the algorithm.
Distributed fiber-optic vibration sensors receive extensive investigation and play a significant role in the sensor panorama. A fiber optic perimeter detection system based on all-fiber interferometric sensor is proposed, through the back-end analysis, processing and intelligent identification, which can distinguish effects of different intrusion activities. In this paper, an intrusion recognition based on the auditory selective attention mechanism is proposed. Firstly, considering the time-frequency of vibration, the spectrogram is calculated. Secondly, imitating the selective attention mechanism, the color, direction and brightness map of the spectrogram is computed. Based on these maps, the feature matrix is formed after normalization. The system could recognize the intrusion activities occurred along the perimeter sensors. Experiment results show that the proposed method for the perimeter is able to differentiate intrusion signals from ambient noises. What’s more, the recognition rate of the system is improved while deduced the false alarm rate, the approach is proved by large practical experiment and project.
This paper researches on the key and difficult issues in stereo measurement deeply, including camera calibration, feature extraction, stereo matching and depth computation, and then put forwards a novel matching method combined the seed region growing and SIFT feature matching. It first uses SIFT characteristics as matching criteria for feature points matching, and then takes the feature points as seed points for region growing to get better depth information. Experiments are conducted to validate the efficiency of the proposed method using standard matching graphs, and then the proposed method is applied to dimensional measurement of mechanical parts. The results show that the measurement error is less than 0.5mm for medium sized mechanical parts, which can meet the demands of precision measurement.
All-fiber interferometer sensor system is a new type of system, which could be used in long-distance, strong-EMI condition for monitoring and inspection. A fiber optic perimeter detection system based on all-fiber interferometric sensor is proposed, through the back-end analysis, processing and intelligent identification, which can distinguish effects of different intrusion activities. In this paper, the universal steps in triggering pattern recognition is introduced, which includes signal characteristics extracting by accurate endpoint detecting, templates establishing by training, and pattern matching. By training the samples acquired in the laboratory, this paper uses the wavelet transformation to decompose the detection signals of the intrusion activities into sub-signals in different frequency bands with multi-resolution analysis. Then extracts the features of the above mentioned intrusions signals by frequency band energy and wavelet information entropy and the system could recognize the intrusion activities occurred along the perimeter sensors. Experiment results show that the proposed method for the perimeter is able to differentiate intrusion signals from ambient noises such as windy and walk effectively. What’s more, the recognition rate of the system is improved while deduced the false alarm rate, the approach is proved by large practical experiment and project.
Distributed optic fiber sensor is a new type of system, which could be used in the long-distance and strong-EMI condition for monitoring and inspection. A method of external modulation with a phase modulator is proposed in this paper to improve the positioning accuracy of the disturbance in a distributed optic-fiber sensor. We construct distributed disturbance detecting system based on Michelson interferometer, and a phase modulator has been attached to the fiber sensor in front of the Faraday rotation mirror (FRM), to elevate the signal produced by interfering of the two lights reflected by the Faraday rotation Mirror to a high frequency, while other signals remain in the low frequency. Through a high pass filter and phase retrieve circus, a signal which is proportional to the external disturbance is acquired. The accuracy of disturbance positioning with this signal can be largely improved. The method is quite simple and easy to achieve. Theoretical analysis and experimental results show that, this method can effectively improve the positioning accuracy.
Proc. SPIE. 8921, MIPPR 2013: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications
KEYWORDS: Target detection, Information fusion, Eye, Visual process modeling, Detection and tracking algorithms, Remote sensing, Biomimetics, Data processing, Mahalanobis distance, Information operations
Aimed to the limitation of present anomaly detection algorism under clutter background for multi-spectral remote sensing data, especially for the situations of dense spread target and exist different attributive of background objects, a bio-inspired anomaly detection algorithm was proposed. Simulate the information processing and fusion mechanism of fly multi-apertures vision system, multi-level background model was proposed to analysis and describe feature of clutter background. Then the threshold value can be chose adaptively according to the level of background model. The proposed algorithm didn’t need the prior knowledge about anomaly, and avoids the choosing of the background widow size. A fusion mechanism was proposed to fuse the different detection results with different level background model. Simulation experiment validated the effectiveness of proposed method.