scholarly journals A Fast Selection Method of Landmarks for Terrain Matching Navigation

2020 ◽  
Vol 38 (5) ◽  
pp. 959-964
Author(s):  
Huaxia Wang ◽  
Yongmei Cheng ◽  
Nan Liu ◽  
Shun Yao ◽  
Juanjuan Ma ◽  
...  
Keyword(s):  
Computational Complexity ◽  
Frequency Domain ◽  
Detection Method ◽  
Saliency Detection ◽  
Statistical Significance ◽  
Correlation Method ◽  
Selection Method ◽  
Landmark Selection ◽  
Saliency Analysis ◽  
Terrain Matching

Under fixed imaging conditions, the landmark selection method based feature traversal analysis has high computational complexity. The hierarchical statistical significance detection method uses global statistical information for feature analysis to overcome the computational complexity problem caused by feature traversal analysis. The frequency domain de-correlation method can remove repeat mode in the image by adaptive Gaussian filtering on the amplitude-frequency characteristics. In this paper, combined the hierarchical statistical saliency detection method with the frequency domain de-correlation method, a fast landmark selection algorithm based on saliency analysis is proposed. Based on the proposed algorithm, the automatic landmark selection architecture for terrain matching navigation was constructed. The selection of landmark points was carried out in the Qin-ling Mountains and the Guangdong and Guangxi hills. The results show that compared with the feature or pixel-based landmark selection method, the landmark selection efficiency of the proposed method is improved by 2 to 3 orders of magnitude. The correct matching rate of candidate landmarks selected in the Qinling Mountains and the Guangdong and Guangxi hills are 73.9% and 88.3% respectively.

scholarly journals A Novel Gesture Recognition System Based on CSI Extracted from a Smartphone with Nexmon Firmware

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 222
Author(s):  
Tao Li ◽  
Chenqi Shi ◽  
Peihao Li ◽  
Pengpeng Chen
Keyword(s):  
Frequency Domain ◽  
Gesture Recognition ◽  
Channel State Information ◽  
Cross Correlation ◽  
Recognition Accuracy ◽  
Correlation Method ◽  
Bottom Layer ◽  
Recognition System ◽  
Channel State ◽  
State Information

In this paper, we propose a novel gesture recognition system based on a smartphone. Due to the limitation of Channel State Information (CSI) extraction equipment, existing WiFi-based gesture recognition is limited to the microcomputer terminal equipped with Intel 5300 or Atheros 9580 network cards. Therefore, accurate gesture recognition can only be performed in an area relatively fixed to the transceiver link. The new gesture recognition system proposed by us breaks this limitation. First, we use nexmon firmware to obtain 256 CSI subcarriers from the bottom layer of the smartphone in IEEE 802.11ac mode on 80 MHz bandwidth to realize the gesture recognition system’s mobility. Second, we adopt the cross-correlation method to integrate the extracted CSI features in the time and frequency domain to reduce the influence of changes in the smartphone location. Third, we use a new improved DTW algorithm to classify and recognize gestures. We implemented vast experiments to verify the system’s recognition accuracy at different distances in different directions and environments. The results show that the system can effectively improve the recognition accuracy.

A numerical and experimental implementation and integration of Steiglitz–McBride algorithm with the frequency domain IIR filtering technique for active vibration control

2016 ◽  
Vol 24 (6) ◽  
pp. 1086-1100
Author(s):  
Utku Boz ◽  
Ipek Basdogan
Keyword(s):  
Computational Complexity ◽  
Vibration Control ◽  
Frequency Domain ◽  
Impulse Response ◽  
Time Domain ◽  
Vibration Suppression ◽  
Active Vibration Control ◽  
Infinite Impulse Response ◽  
Iir Filter ◽  
Active Vibration

In adaptive control applications for noise and vibration, finite ımpulse response (FIR) or ınfinite ımpulse response (IIR) filter structures are used for online adaptation of the controller parameters. IIR filters offer the advantage of representing dynamics of the controller with smaller number of filter parameters than with FIR filters. However, the possibility of instability and convergence to suboptimal solutions are the main drawbacks of such controllers. An IIR filtering-based Steiglitz–McBride (SM) algorithm offers nearly-optimal solutions. However, real-time implementation of the SM algorithm has never been explored and application of the algorithm is limited to numerical studies for active vibration control. Furthermore, the prefiltering procedure of the SM increases the computational complexity of the algorithm in comparison to other IIR filtering-based algorithms. Based on the lack of studies about the SM in the literature, an SM time-domain algorithm for AVC was implemented both numerically and experimentally in this study. A methodology that integrates frequency domain IIR filtering techniques with the classic SM time-domain algorithm is proposed to decrease the computational complexity. Results of the proposed approach are compared with the classical SM algorithm. Both SM and the proposed approach offer multimodal vibration suppression and it is possible to predict the performance of the controller via simulations. The proposed hybrid approach ensures similar vibration suppression performance compared to the classical SM and offers computational advantage as the number of control filter parameters increases.

An improved saliency detection method based on non-uniform quantification and channel-weighted color distance

2016 ◽  
Vol 76 (8) ◽  
pp. 11037-11050 ◽  
Author(s):  
Aili Han ◽  
Feilin Han ◽  
Jing Hao ◽  
Yahui Yuan
Keyword(s):  
Detection Method ◽  
Saliency Detection

A real time detection method for abnormal strapping of steel coil based on CCD active imaging

2021 ◽  
Author(s):  
Chuan Ye ◽  
Liming Zhao ◽  
Qiyan Wang ◽  
Bo Pan ◽  
Youchun Xie ◽  
...  
Keyword(s):  
Maximum Entropy ◽  
Detection Method ◽  
Saliency Detection ◽  
Automatic Segmentation ◽  
Engineering Application ◽  
Detection Accuracy ◽  
Steel Coil ◽  
Detection Model ◽  
Laser Stripe ◽  
Active Imaging

Abstract In order to accurately detect the abnormal looseness of strapping in the process of steel coil hoisting, an accurate detection method of strapping abnormality based on CCD structured light active imaging is proposed. Firstly, a maximum entropy laser stripe automatic segmentation model integrating multi-scale saliency features is constructed. With the help of saliency detection model, the purpose is to reduce the interference of the environment to the laser stripe and highlight the distinguishability between the stripe and the background. Then, the maximum entropy is used to segment the fused saliency features and accurately extract the stripe contour. Finally, the stripe normal field is obtained by calculating the stripe gradient vector, the stripe center line is extracted based on the stripe distribution normal direction, and the abnormal strapping is recognized online according to the stripe center. Experiments show that the proposed method is effective in terms of detection accuracy and time efficiency, and has certain engineering application value.

A Frequency-Domain-Based Algorithm for Detecting Microseismicity Using Dense Surface Seismic Arrays

2021 ◽  
Author(s):  
Maria Mesimeri ◽  
Kristine L. Pankow ◽  
James Rutledge
Keyword(s):  
Frequency Domain ◽  
Detection Method ◽  
Maximum Amplitude ◽  
High Energy ◽  
Aftershock Sequence ◽  
Anthropogenic Activity ◽  
Small Scale ◽  
Seismic Events ◽  
Small Magnitude ◽  
Seismic Arrays

ABSTRACT We propose a new frequency-domain-based algorithm for detecting small-magnitude seismic events using dense surface seismic arrays. Our proposed method takes advantage of the high energy carried by S waves, and approximate known source locations, which are used to rotate the horizontal components to obtain the maximum amplitude. By surrounding the known source area with surface geophones, we achieve a favorable geometry for locating the detected seismic events with the backprojection method. To test our new detection method, we used a dense circular array, consisting of 151 5 Hz three-component geophones, over a 5 km aperture that was in operation at the Utah Frontier Observatory for Research in Geothermal Energy (FORGE) in southcentral Utah. We apply the new detection method during a small-scale test injection phase at FORGE, and during an aftershock sequence of an Mw 4.1 earthquake located ∼30  km north of the geophone array, within the Black Rock volcanic field. We are able to detect and locate microseismic events (Mw<0) during injections, despite the high level of anthropogenic activity, and several aftershocks that are missing from the regional catalog. By comparing our method with known algorithms that operate both in the time and frequency domain, we show that our proposed method performs better in the case of the FORGE injection monitoring, and equally well for the off-array aftershock sequence. Our new method has the potential to improve microseismic event detections even in extremely noisy environments, and the proposed location scheme serves as a direct discriminant between true and false detections.

scholarly journals Ship Detection in Panchromatic Optical Remote Sensing Images Based on Visual Saliency and Multi-Dimensional Feature Description

2020 ◽  
Vol 12 (1) ◽  
pp. 152 ◽  
Author(s):  
Ting Nie ◽  
Xiyu Han ◽  
Bin He ◽  
Xiansheng Li ◽  
Hongxing Liu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Fourier Transform ◽  
Detection Method ◽  
Saliency Detection ◽  
Visual Saliency ◽  
Saliency Map ◽  
False Alarms ◽  
Optical Remote Sensing ◽  
Remote Sensing Images ◽  
Ship Detection

Ship detection in panchromatic optical remote sensing images is faced with two major challenges, locating candidate regions from complex backgrounds quickly and describing ships effectively to reduce false alarms. Here, a practical method was proposed to solve these issues. Firstly, we constructed a novel visual saliency detection method based on a hyper-complex Fourier transform of a quaternion to locate regions of interest (ROIs), which can improve the accuracy of the subsequent discrimination process for panchromatic images, compared with the phase spectrum quaternary Fourier transform (PQFT) method. In addition, the Gaussian filtering of different scales was performed on the transformed result to synthesize the best saliency map. An adaptive method based on GrabCut was then used for binary segmentation to extract candidate positions. With respect to the discrimination stage, a rotation-invariant modified local binary pattern (LBP) description was achieved by combining shape, texture, and moment invariant features to describe the ship targets more powerfully. Finally, the false alarms were eliminated through SVM training. The experimental results on panchromatic optical remote sensing images demonstrated that the presented saliency model under various indicators is superior, and the proposed ship detection method is accurate and fast with high robustness, based on detailed comparisons to existing efforts.

Sign in / Sign up

Export Citation Format

Share Document