Real-time target detection technique for metal detector arrays: an image processing approach

1999 ◽  
Author(s):  
Kevin L. Russell ◽  
Yogadhish Das ◽  
John E. McFee ◽  
Robert Chesney
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Target Detection ◽  
Detection Technique ◽  
Metal Detector ◽  
Detector Arrays ◽  
Processing Approach

scholarly journals Automatic Acoustic Target Detecting and Tracking on the Azimuth Recording Diagram with Image Processing Methods

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5391
Author(s):  
Fan Yin ◽  
Chao Li ◽  
Haibin Wang ◽  
Fan Yang
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Target Detection ◽  
Ambient Noise ◽  
Arrival Direction ◽  
Processing Methods ◽  
Acoustic Target ◽  
Real Time Tracking ◽  
Passive Acoustic ◽  
Target Detecting

Passive acoustic target detection has been a hot research topic for a few decades. Azimuth recording diagram is one of the most promising techniques to estimate the arrival direction of the interested signal by visualizing the sound wave information. However, this method is challenged by the random ambient noise, resulting in low reliability and short effective distance. This paper presents a real-time postprocessing framework for passive acoustic target detection modalities by using a sonar array, in which image processing methods are used to automate the target detecting and tracking on the azimuth recording diagram. The simulation results demonstrate that the proposed approach can provide a higher reliability compared with the conventional ones, and is suitable for the constraints of real-time tracking.

scholarly journals Vehicle Vacant Seat Identification and Mask Detection using Image processing

2021 ◽  
Vol 9 (VII) ◽  
pp. 118-121
Author(s):  
Mr. Shubham Ingole
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Face Detection ◽  
Detection Technique ◽  
Processing Technology ◽  
Raspberry Pi ◽  
Human Being ◽  
People Tracking ◽  
Software Application ◽  
The Face

This article describes the technique of real-time face detection, mask detection, and vacant seat available in the vehicle. There are so many technologies for finding seat availability in the vehicle. But image processing technology is very popular today. Face detection is part of image processing. It is used to find the face of a human being in a certain area. Face detection is used in many applications, such as facial recognition, people tracking or photography. In this paper, the face detection technique is used to detect the vacant seat availability in the vehicle and also to detect whether the passenger wear the mask on his face or not. The webcam is installed in the vehicle and connected with the Raspberry Pi 3 model B. When the vehicle leaves the station, the webcam will capture images of the passengers in the seating area. The webcam will be mounted on the vehicle. The images will be adjusted and enhanced to reduce noise made by the software application. The system obtains the maximum number of passengers in the vehicle that processes the images and then calculates the availability of seats in the vehicle. In covid-19 situation mask detection is necessary. so this system also used to detect the mask on face.

Design of a New Image Processing System Based on FPGA

2014 ◽  
Vol 1003 ◽  
pp. 216-220 ◽  
Author(s):  
Qi Li ◽  
Yu Yang ◽  
Zhong Ke Li ◽  
Jing Lu
Keyword(s):  
Image Processing ◽  
Unmanned Aerial Vehicles ◽  
Real Time ◽  
Target Detection ◽  
Processing System ◽  
Image Processing Algorithm ◽  
Verilog Hdl ◽  
Video Decoding ◽  
Image Processing System ◽  
Aerial Vehicles

According to the unmanned aerial vehicles real-time video image acquiring and target detection requirements, an image processing system was designed based on FPGA and TVP5150A decoder, and the video decoding hardware and software was also designed to meet the demands of unmanned aerial vehicles. An I2C controller was realized to assure the implementation of video decoding process in accordance with the requirements, and an image processing algorithm and applied to the image recognition process. Both of these were completed in FPGA using verilog HDL language. The correction of this image processing system was verified through real-time experiments.

An image processing approach for two-phase interfaces visualized by a real time neutron radiography technique

1998 ◽  
Vol 9 (4) ◽  
pp. 203-210 ◽  
Author(s):  
Keiichi Uchimura ◽  
Glenn D. Harvel ◽  
Takaaki Matsumoto ◽  
Masayuki Kanzaki ◽  
Jen-Shih Chang
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Neutron Radiography ◽  
Two Phase ◽  
Processing Approach

scholarly journals Differentiating Birds and Animals using Deep Learning Neural Network with Image Processing Approach

2020 ◽  
Vol 5 (9) ◽  
pp. 609-613
Author(s):  
K Pandiaraj ◽  
P Sivakumar ◽  
V Nandhini ◽  
S Parkav
Keyword(s):  
Neural Network ◽  
Image Processing ◽  
Deep Learning ◽  
Real Time ◽  
The Real ◽  
Processing Approach ◽  
Human Effort ◽  
Deep Learning Neural Network

In farms we can see that the birds and animals destroying the crops. The movement of birds and animals cannot be controlled by any method. We can only drive away them. To drive away them, humans are used. To reduce the human effort we have introduced a method using image processing. In this method, the real time images are given as input and sound will be derived as output. The image given as input is compared with the trained images and classified into birds and animals. After the identification, birds can be driven away by using cracker sound and animals can be driven away by using a human sound.

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