scholarly journals DESIGN AND IMPLEMENTATION OF ANTI-TANK GUIDED-MISSILE (ATGM) CONTROL SYSTEM USING SEMI-AUTOMATIC COMMAND LINE OF SIGHT (SACLOS) METHOD BASED ON DIGITAL IMAGE PROCESSING

2021 ◽  
Vol 7 (2) ◽  
pp. 217
Author(s):  
Muhammad Hanifudin Al Fadli ◽  
Dadang Gunawan ◽  
Romie Oktovianus Bura ◽  
Larasmoyo Nugroho
Keyword(s):  
Image Processing ◽  
Control System ◽  
Tracking System ◽  
Color Space ◽  
Raspberry Pi ◽  
Infrared Lamp ◽  
Syrian Civil War ◽  
High Level ◽  
Infrared Tracking ◽  
Coordinate Data

<div><p class="Els-history-head">The Anti-Tank Guided-Missile (ATGM) system has a very important role in the modern battlefield. This system proved its effectiveness in many modern conflicts such as the Syrian Civil War and Nagorno-Karabakh War. The ATGM system has a very simple electronic and mechanism but it has a very high level of accuracy and precision. One of the control methods used in ATGM is SACLOS method. This method tracks missile position by detecting an infrared lamp that is placed on the missile tail. The tracking system sends control signals to the missile as a result of the correction of the missile position when flying. The infrared tracking system in this research was made using a modified OV5647 camera with the addition of a 940 nm narrow bandpass filter. There are 3 cameras with 1x, 8x, and 16x magnifications which are accessed using 3 Raspberry Pi boards. X and y coordinate data of the infrared lamp is sent to the airframe using wireless telemetry. Atmega328 microcontroller process x and y coordinate data into input proportional control. The result of this research is the prototype of an anti-tank missile control system with an infrared tracking instrument capable track a series of 88 infrared LEDs as far as 997.16 meters with a tracking speed of 90.11 FPS. The threshold parameters of image processing using luminance of YUV color space has a range of 240-255. The control parameter Kp=7 is used in wind tunnel testing with airspeed 20 m/s capable of directing airframe motion to the telescope's crosshairs.</p></div>

scholarly journals Eye Tracking ,Control Gestures, Raspberry Pi, Image Processing.

2019 ◽  
pp. 311-319
Author(s):  
Arulmozhi. K ◽  
Dharshini. K ◽  
Kaviyasree. P ◽  
Seetha. J
Keyword(s):  
Image Processing ◽  
Control System ◽  
Eye Tracking ◽  
Eye Movement ◽  
Tracking Control ◽  
Tracking System ◽  
Raspberry Pi ◽  
Cursor Control ◽  
Design And Implementation ◽  
Processing Module

Smart eye tracking system is designed for controlling any devices which has digital screen, with the eye ball movements and gestures without the help of required hardware. This paper proposes the design and implementation of cursor control system based on the movement of the eye ball. Then the movement of the eye ball is tracked and the cursor movement is regulated accordingly and gestures like blinking enables enter and blinking twice enables right click and left click. These gestures and tracking system enables the users to use the entire device. The image processing module consists of webcam and python customized image processing, the eye movement image is captured and transmitted to Raspberry pi 3 model B version 2 microcontroller for processing with open CV to derive the coordinate of eyeball. The coordinate of eyeball is utilized for cursor control on the Raspberry pi screen to control the system.

scholarly journals HVAC and Audio Control System using Gesture Recognition in Cars

2020 ◽  
Vol 9 (3) ◽  
pp. 3193-3196
Keyword(s):  
Image Processing ◽  
Control System ◽  
Gesture Recognition ◽  
Background Subtraction ◽  
Advanced Technology ◽  
Raspberry Pi ◽  
Hvac System ◽  
Hand Gestures ◽  
Hand Part ◽  
Free Interaction

Gesture recognition technology entails a wide variety of touch-free interaction capabilities which controls notably contribute to easing our interaction with devices, reducing the need for a keys, or button. To recognize the different hand gestures for different control system in cars is done through image processing. A new method for the hand gestures is that, the hand part gets extracted from the background using background subtraction algorithm using raspberry pi, there is no need of buttons for using of some equipments in different vehicles by using an advanced technology. In gesture recognition technology we can control the audio and HVAC system automatically instead of searching for a particular button, which causes distraction while driving.

Development of a Tracking System on the Mobile Robot

2015 ◽  
Vol 764-765 ◽  
pp. 680-684
Author(s):  
Kuo Lan Su ◽  
Jr Hung Guo ◽  
Kuo Hsien Hsia
Keyword(s):  
Image Processing ◽  
Control System ◽  
Mobile Robot ◽  
Pid Control ◽  
Balance Control ◽  
Tracking System ◽  
Control Law ◽  
Moving Target ◽  
System A ◽  
Feedback Data

The purpose of this paper is to develop an intelligent mobile robot using image processing technology. The mobile robot is composed of a visual tracking system, a loading platform, a balance control system, a PC-based controller, four ultrasonic sensors and a power system. We develop a PC based control system for image processing and path planning. The mobile robot can track a moving target and adjust the loading platform by the balance control system simultaneously. The Image processing based on OpenCV use two different tracking methods, MTLT (Match Template Learning Tracking) and TLD (Tracking, Learning and Detection), to track moving targets. The efficiencies of both methods for tracking the moving target on the mobile robot are compared in this paper. The loading platform control system uses HOLTEK Semiconductor Company's HT66F Series 8-bit microprocessor as the processor, and receives the feedback data from the FAS-A inclinometer sensor. The controller of the loading platform uses the PID control law according to the feedback signals of the inclinometer sensor, and controls the rotation speed of the platform motor to tune the balance level. Keywords— Intelligent mobile robot, Image processing, OpenCV, MTLT, TLD, HOLTEK, FAS-A inclinometer sensor, PID control.

scholarly journals Development of Conventional Controller Based on Image Processing for Monitoring and Controlling Burning Zone Temperature in a Cement Plant in Rotary Kiln Process Through IOT

2021 ◽  
Vol 20 (4) ◽  
pp. 209-214
Author(s):  
Polaiah Bojja ◽  
N. Merrin Prasanna ◽  
Pamula Raja Kumari ◽  
T. Bhuvanendhiran ◽  
Panuganti Jayanth Kumar
Keyword(s):  
Image Processing ◽  
Rotary Kiln ◽  
Continuous Process ◽  
Color Space ◽  
Threshold Value ◽  
Cement Industry ◽  
Raspberry Pi ◽  
Python Language ◽  
Burning Zone ◽  
Processing Techniques

In the cement factories, a rotary kiln is a pyro-processing device that is used to raise the temperature of the materials in a continuous process. Temperature monitoring is an essential process in the rotary kiln to yield high quality clinker and it has been implemented using various image processing techniques. In this paper we are measuring and controlling the temperature of rotational kiln in cement industry to get proper clinker ouput. Burning zone flame images are captured using CCD(Charge Coupled Device) camera and are processed using image processing with PID(Proportion Integration and Derivative) controller and which are programmed on raspberry pi card with the help of python language, also the captured images and attributes are transferred to authorized mobile/pc through Raspberry PI by selecting the IP address of mobile or PC. All the attributes received in the mobile in the form of web page the according to the object following data temperature controlled and object is ceaselessly followed to get the proper clinker output. Picture handling calculation with Open cv, as indicated by the calculation the edge estimation of the camera is settled. The frame value of the camera is set. Conversion from RGB color space to HSV color space is achieved and the reference color threshold value is determined. The range esteem estimated by the camera is contrasted and the reference esteem. In this study temp of rotational kiln is measured effectively using PID controller, this controller continuously control the temperature of revolving kiln by varying the i/p images of burning zone at finally fix one flame which is giving 1400degc.

DEVELOPMENT OF TRACKING SYSTEM FOR MOBILE ROBOT USING IMAGE RECOGNITION ALGORITHMS

2015 ◽  
Vol 39 (3) ◽  
pp. 501-513 ◽  
Author(s):  
Kuo-Lan Su ◽  
Bo-Yi Li ◽  
Kuo-Hsien Hsia
Keyword(s):  
Image Processing ◽  
Control System ◽  
Mobile Robot ◽  
Pid Control ◽  
Balance Control ◽  
Tracking System ◽  
Control Law ◽  
Moving Target ◽  
Image System ◽  
System A

In this paper, an intelligent mobile robot using image processing technology is developed. The mobile robot contains an image system, a loading platform, a balance control system, a PC-based controller, four ultrasonic sensors and a power system. We develop a PC-based control system for image processing and path planning. The mobile robot can track a moving target and adjust the loading platform by the balance control system simultaneously. The image processing based on OpenCV uses two different tracking methods to track moving targets: MTLT (Match Template Learning Tracking) and TLD (Tracking, Learning and Detection). The efficiency of both methods for tracking the moving target on the mobile robot is compared here. The balance control system, with a HOLTEK Semiconductor Company’s HT66F Series 8-bit microprocessor as the processor, uses the PID control law according to the feedback signals of the inclinometer sensor to control the balance level of the loading platform.

scholarly journals Embedded image processing on Raspberry Pi connected to the industrial control system

2019 ◽  
Vol 2 (1) ◽  
pp. 62-71
Author(s):  
Jozef Hrbček ◽  
Emília Bubeníková
Keyword(s):  
Image Processing ◽  
Control System ◽  
Real Time ◽  
Image Data ◽  
Raspberry Pi ◽  
Processing Unit ◽  
Industrial Control System ◽  
Industrial Control ◽  
Industrial Automation ◽  
Embedded Image

Abstract This paper deals with the image processing from the camera for Raspberry Pi connected with real-time communication network to the control system (PLC). The low time delay for receiving and sending commands, data, etc. is very important in the automating production processes. This can be provided by industrial real-time network based on Ethernet. The Ethernet POWERLINK, which is supported on B&R PLCs, is one of them. It is a simple solution for a variety of applications because the POWERLINK is publicly available as the open source. Connecting the PLC and Raspberry Pi with Ethernet POWERLINK opens up many applications in industrial automation. For example, image data obtained using a camera attached to Raspberry Pi can be used to sense image of manufacturing processes and products and evaluate their quality in industrial automation. This article focuses on an image processing unit and the PLC system with CPU redundancy used in the industrial application. Vision systems are often used to improve products quality control, saving costs and time.

scholarly journals Automatic Extraction of Color Features from Landscape Images Based on Image Processing

2021 ◽  
Vol 38 (3) ◽  
pp. 747-755
Author(s):  
Cong Tan ◽  
Shaoyu Yang
Keyword(s):  
Image Processing ◽  
Color Space ◽  
Color Constancy ◽  
Support Vector ◽  
Automatic Extraction ◽  
Color Features ◽  
Image Library ◽  
Presentation Effect ◽  
High Level

The dominant color features determine the presentation effect and visual experience of landscapes. The existing studies rarely quantify the application effect of landscape colors through image colorization. Besides, it is unreasonable to analyze landscape images with multiple standard colors with a single color space. To solve the problem, this paper proposes an automatic extraction method for color features from landscape images based on image processing. Firstly, a landscape lighting model was constructed based on color constancy theories, and the quality of landscape images was improved with color constant image enhancement technology. In this way, the low-level color features were extracted from the landscape image library. Next, support vector machine (SVM) and fuzzy c-means (FCM) were innovatively integrated to extract high-level color features from landscape images. The proposed method was proved effective through experiments.

scholarly journals IoT Based Traffic Control System using Image Processing

2021 ◽  
Vol 9 (VII) ◽  
pp. 317-321
Author(s):  
Mr. Sachin Tyagi
Keyword(s):  
Image Processing ◽  
Control System ◽  
Real Time ◽  
Traffic Control ◽  
Traffic Management ◽  
Raspberry Pi ◽  
Traffic System ◽  
Traffic Efficiency ◽  
Real Time Traffic ◽  
Traffic Control System

In the current scenario we can see that the traffic jam has become a serious problem in rapidly growing cities (As per their population) of India by which there is increase in air pollution, Fuel consumption as well as vehicular density. So there is a requirement to find a new way for traffic controlling traffic system which will be managed through real time IoT based traffic control system using image processing. This is a smart traffic management system that is designed to control real time traffic system which consist of components of Raspberry Pi, Pi camera. Raspberry pi is the key component which is used to control all performance multitasking. By using cameras, we monitor different lanes constantly. Image processing is used to examine detection and counting no. of vehicles in different lanes. It increases the traffic efficiency and clearance. The signal light will be decided as per the no. of vehicle count using image processing.

Design and Simulation of Smart Control System for Internet Traffic Distribution on Servers by Using Fuzzy Logic System

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Raid Daoud ◽  
Yaareb Al-Khashab
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Input Parameter ◽  
Traffic Density ◽  
The Internet ◽  
Linguistic Variables ◽  
Internet Service ◽  
Traffic Distribution ◽  
Smart Control ◽  
High Level

The internet service is provided by a given number of servers located in the main node of internet service provider (ISP). In some cases; the overload problem was occurred because a demand on a given website goes to very high level. In this paper, a fuzzy logic control (FLC) has proposed to distribute the load into the internet servers by a smart and flexible manner. Three effected parameters are tacked into account as input for FLC: link capacity which has three linguistic variables with Gaussian membership function (MF): (small, medium and big), traffic density with linguistic variables (low, normal and high) and channel latency with linguistic variables (empty, half and full); with one output which is the share server status (single, simple and share). The proposed work has been simulated by using MATLAB 2016a, by building a structure in the Fuzzy toolbox. The results were fixed by two manners: the graphical curves and the numerical tables, the surface response was smoothly changed and translates the well-fixed control system. The numerical results of the control system satisfy the idea of the smart rout for the incoming traffics from the users to internet servers. So, the response of the proposed system for the share of server ratio is 0.122, when the input parameter in the smallest levels; and the ratio is 0.879 when the input parameters are in highest level. The smart work and flexible use for the FLC is the main success solution for most of today systems control.

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