scholarly journals Object Detection Robot Using Fuzzy Logic Controller Through Image Processing

2021 ◽  
Vol 1737 (1) ◽  
pp. 012045
Author(s):  
M Khairudin ◽  
S Yatmono ◽  
AC Nugraha ◽  
M Ikhsani ◽  
A Shah ◽  
...  
Keyword(s):  
Image Processing ◽  
Fuzzy Logic ◽  
Object Detection ◽  
Fuzzy Logic Controller

Digital Image Processing for Detecting and Classifying Plant Diseases

2017 ◽  
Vol 2 (11) ◽  
pp. 1-7
Author(s):  
Izay A. ◽  
Onyejegbu L. N.
Keyword(s):  
Image Processing ◽  
Fuzzy Logic ◽  
Programming Language ◽  
Design Methodology ◽  
Fuzzy Logic Controller ◽  
Object Oriented ◽  
Plant Diseases ◽  
Analysis And Design ◽  
Crop Diseases ◽  
Growing Population

Agriculture is the backbone of human sustenance in this world. With growing population, there is need for increased productivity in agriculture to be able to meet the demands. Diseases can occur on any part of a plant, but in this paper only the symptoms in the fruits of a plant is considered using segmentation algorithm and edge/ sizing detectors. We also looked at image processing using fuzzy logic controller. The system was designed using object oriented analysis and design methodology. It was implemented using MySQL for the database, and PHP programming language. This system will be of great benefit to farmers and will encourage them in investing their resources since crop diseases can be detected and eliminated early.

An Advanced Fuzzy Logic Based Traffic Controller

2014 ◽  
Vol 5 (1) ◽  
pp. 31-40
Author(s):  
Bilal Ahmed Khan ◽  
Nai Shyan Lai
Keyword(s):  
Image Processing ◽  
Fuzzy Logic ◽  
Traffic Management ◽  
Fuzzy Logic Controller ◽  
Current Model ◽  
Traffic Signals ◽  
Processing Technique ◽  
Urban Traffic ◽  
Image Processing Technique ◽  
Traffic Light

Traffic light plays an important role in the urban traffic management. Therefore, it is necessary to improve the traffic controller for effective traffic management and better traffic flow leading to greener environment. In this paper, an advanced and intelligent traffic light controller is proposed, utilising the fuzzy logic technology and image processing technique. A fuzzy logic control has been implemented to provide the attribute of intelligence to the system. For real-time image acquisition, the process is further linked to the fuzzy logic controller which generates a unique output for each input pattern. Here image processing and fuzzy logic tool boxes of MATLAB are used where the final output is sent to Peripheral Interface Controller (PIC) microcontroller to drive the traffic signals in the desired manner. The results obtained show an improvement of 44% in the overall outcome of traffic management as compared to the conventional traffic controller, marking great feasibility and practicality of the current model.

An Advanced Fuzzy Logic Based Traffic Controller

2015 ◽  
pp. 1490-1499
Author(s):  
Bilal Ahmed Khan ◽  
Nai Shyan Lai
Keyword(s):  
Image Processing ◽  
Fuzzy Logic ◽  
Traffic Management ◽  
Fuzzy Logic Controller ◽  
Current Model ◽  
Traffic Signals ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Traffic Light ◽  
Logic Control

Traffic light plays an important role in the urban traffic management. Therefore, it is necessary to improve the traffic controller for effective traffic management and better traffic flow leading to greener environment. In this paper, an advanced and intelligent traffic light controller is proposed, utilising the fuzzy logic technology and image processing technique. A fuzzy logic control has been implemented to provide the attribute of intelligence to the system. For real-time image acquisition, the process is further linked to the fuzzy logic controller which generates a unique output for each input pattern. Here image processing and fuzzy logic tool boxes of MATLAB are used where the final output is sent to Peripheral Interface Controller (PIC) microcontroller to drive the traffic signals in the desired manner. The results obtained show an improvement of 44% in the overall outcome of traffic management as compared to the conventional traffic controller, marking great feasibility and practicality of the current model.

scholarly journals Droplet movement control using fuzzy logic controller and image processing along with pin valves inside microfluidic device

2019 ◽  
Vol 52 (9-10) ◽  
pp. 1517-1531 ◽  
Author(s):  
Faisal Mehmood ◽  
Zeeshan Haider ◽  
Umar Farooq ◽  
Yin Baoqun
Keyword(s):  
Image Processing ◽  
Fuzzy Logic ◽  
Microfluidic Device ◽  
Fuzzy Logic Controller ◽  
Active Contours ◽  
Fuzzy Controller ◽  
Microfluidic Channel ◽  
Processing Algorithm ◽  
Image Processing Algorithm ◽  
Droplet Movement

Most of the research studies nowadays are trying to bring automation to biomedical engineering and Lab on a Chip which is fast growing interdisciplinary field and has attracted researchers from various fields. The objective of this paper is to present an overall system to control droplet movement inside microfluidic channel using fuzzy logic controller, image processing algorithm, and microvalves installed within microfluidic channel. A state space model has been derived from circuit analogy approach to describe the microfluidic network. Furthermore, a COMSOL-based study is primed for device structure by means of droplet generation and controlling the droplet through fitted valves. Moreover, an image processing algorithm based on active contours has been proposed in this research to track the movement of the droplet through the channel. This droplet controlling method is utterly based on fuzzy controller as well as camera images to move the droplet at desired position by controlling flow rates inside the fluidic channel using valves installed inside the microfluidic device. The results indicate that the fuzzy logic controller performs much better in terms of stability and faster response as compared to conventional proportional–integral–derivative controller.

scholarly journals Towards the Design and Implementation of an Image-Based Navigation System of an Autonomous Underwater Vehicle Combining a Color Recognition Technique and a Fuzzy Logic Controller

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4053
Author(s):  
Yu-Hsien Lin ◽  
Chao-Ming Yu ◽  
Chia-Yu Wu
Keyword(s):  
Image Processing ◽  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Noise Removal ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Water Tank ◽  
Image Information ◽  
Revolution Speed ◽  
Underwater Object

This study proposes the development of an underwater object-tracking control system through an image-processing technique. It is used for the close-range recognition and dynamic tracking of autonomous underwater vehicles (AUVs) with an auxiliary light source for image processing. The image-processing technique includes color space conversion, target and background separation with binarization, noise removal with image filters, and image morphology. The image-recognition results become more complete through the aforementioned process. After the image information is obtained for the underwater object, the image area and coordinates are further adopted as the input values of the fuzzy logic controller (FLC) to calculate the rudder angle of the servomotor, and the propeller revolution speed is defined using the image information. The aforementioned experiments were all conducted in a stability water tank. Subsequently, the FLC was combined with an extended Kalman filter (EKF) for further dynamic experiments in a towing tank. Specifically, the EKF predicts new coordinates according to the original coordinates of an object to resolve data insufficiency. Consequently, several tests with moving speeds from 0.2 m/s to 0.8 m/s were analyzed to observe the changes in the rudder angles and the sensitivity of the propeller revolution speed.

scholarly journals Autonomous Visual Servoing for Alternately Working Arm Robots

2021 ◽  
Author(s):  
Tresna Dewi ◽  
Rusdianasari Rusdianasari ◽  
RD Kusumanto ◽  
Siproni Siproni ◽  
Fradina Septiarini ◽  
...  
Keyword(s):  
Image Processing ◽  
Fuzzy Logic ◽  
Industry 4.0 ◽  
Visual Servoing ◽  
Fuzzy Logic Controller ◽  
Human Life ◽  
Experimental Results ◽  
Agricultural Products ◽  
Pick And Place ◽  
Time Required

Robots have infiltrated many aspects of human life up to this point, and with the term Industry 4.0, robots have even become the primary workforce in various factories. This condition necessitates that the robots collaborate without clashing. This paper discusses the application of two arm robot manipulators working alternately in sorting agricultural products. The proposed method employs simple image processing to detect the object and becomes the input to the system to control the robots. The effectiveness of the proposed method is enhanced by the application of a Fuzzy Logic Controller to smoothen robots’ joints motions. The average time required by the robot to finish their task from detecting to returning to standby position is 11.76 s for green tomatoes and 12.86 s for red tomatoes. The experimental results show that the proposed method is effective in controlling two robots to pick and place agricultural products using visual servoing.

Industrial IoT enabled fuzzy logic based flame image processing for rotary kiln control

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Merrin Prasanna Nagadasari ◽  
Polaiah Bojja
Keyword(s):  
Image Processing ◽  
Fuzzy Logic ◽  
Temperature Measurement ◽  
Rotary Kiln ◽  
Fuzzy Logic Controller ◽  
High Quality ◽  
Camera System ◽  
Inference System ◽  
Content Type ◽  
Industrial Iot

Purpose A rotary kiln is a pyro processing device that is used to raise the temperature of materials in cement factories. Temperature monitoring is an essential process in the rotary kiln to yield high quality clinker. Temperature measurement is a challenging task in clinkering process and it is difficult to apply automation techniques. As the pyrometer gives unreliable readings, it is necessary to apply various image processing techniques on the camera images to measure the temperature inside the kiln at different zones. Design/methodology/approach In this paper, a fuzzy logic rule-based analysis is proposed to measure temperature using a burning flame image in which it considers red, green, blue (RGB) magnitude planes. The proposed method uses Mamdani fuzzy inference system for decision-making. The system takes RGB magnitude as an input fuzzified variable and generates temperature as fuzzified output. Findings This paper focuses on the temperature measurement obtained from the images of the camera system. The commands to the valves and actuators are controlled using the center of gravity of the control regime. The fuzzy logic controller detects the temperature of flame zones using color features of burning flame images. Originality/value Precise temperature mapping of flame images helps to control the temperature inside the rotating kiln to produce high quality clinker. The process can be viewed remotely and controlled using various control loops from anywhere.

Application Fuzzy Logic System for Accurate Sheet Trim Shower Position

2019 ◽  
Vol 3 (1) ◽  
pp. 186-192
Author(s):  
Yudi Wibawa
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Dc Motor ◽  
Automation System ◽  
Paper Making ◽  
System A ◽  
Accurate Position ◽  
And Performance ◽  
Better Than ◽  
Logic System

This paper aims to study for accurate sheet trim shower position for paper making process. An accurate position is required in an automation system. A mathematical model of DC motor is used to obtain a transfer function between shaft position and applied voltage. PID controller with Ziegler-Nichols and Hang-tuning rule and Fuzzy logic controller for controlling position accuracy are required. The result reference explains it that the FLC is better than other methods and performance characteristics also improve the control of DC motor.

Sign in / Sign up

Export Citation Format

Share Document