A Detection Algorithm for Projectile Target

2014 ◽  
Vol 1044-1045 ◽  
pp. 972-975
Author(s):  
Zai Fei Shang ◽  
Chun Ping Wang

For consistency of performance in the shape of the projectile targets, a projectile target detection algorithm is presented based on HOG (Histogram of Oriented Gradient) characterization algorithm. First, detecting the bullet image corner, and secondly, by Mean-shift algorithm improves the corner position accuracy and reduces the number of corner points, finally, applying support vector machines to extract the projectile targets. Compared with the traditional small target detection algorithm, the algorithm describes the targets more accurately, along with better real-time performance. Simulation, the projectile target detection rate of over 80% and verify the effectiveness of the algorithm.

2015 ◽  
Author(s):  
Ying Zhao ◽  
Gang Liu ◽  
Huixin Zhou ◽  
Hanlin Qin ◽  
Xiao Li ◽  
...  

2018 ◽  
Vol 5 (9) ◽  
pp. 180160 ◽  
Author(s):  
Jian-hong Yang ◽  
Huai-ying Fang ◽  
Ren-cheng Zhang ◽  
Kai Yang

Arc faults in low-voltage electrical circuits are the main hidden cause of electric fires. Accurate identification of arc faults is essential for safe power consumption. In this paper, a detection algorithm for arc faults is tested in a low-voltage circuit. With capacitance coupling and a logarithmic detector, the high-frequency radiation characteristics of arc faults can be extracted. A rapid method for computing the current waveform slope characteristics of an arc fault provides another characteristic. Current waveform periodic integral characteristics can be extracted according to asymmetries of the arc faults. These three characteristics are used to develop a detection algorithm of arc faults based on multiinformation fusion and support vector machine learning models. The tests indicated that for series arc faults with single and combination loads and for parallel arc faults between metallic contacts and along carbonization paths, the recognition algorithm could effectively avoid the problems of crosstalk and signal loss during arc fault detection.


Sign in / Sign up

Export Citation Format

Share Document