scholarly journals Design and development of DrawBot using image processing

2022 ◽  
Vol 12 (1) ◽  
pp. 365
Author(s):  
Krithika Vaidyanathan ◽  
Nandhini Murugan ◽  
Subramani Chinnamuthu ◽  
Sivashanmugam Shivasubramanian ◽  
Surya Raghavendran ◽  
...  
Keyword(s):  
Image Processing ◽  
Inverse Kinematics ◽  
Control Algorithm ◽  
Input Image ◽  
Design And Development ◽  
Matlab Simulink

Extracting text from an image and reproducing them can often be a laborious task. We took it upon ourselves to solve the problem. Our work is aimed at designing a robot which can perceive an image shown to it and reproduce it on any given area as directed. It does so by first taking an input image and performing image processing operations on the image to improve its readability. Then the text in the image is recognized by the program. Points for each letter are taken, then inverse kinematics is done for each point with MATLAB/Simulink and the angles in which the servo motors should be moved are found out and stored in the Arduino. Using these angles, the control algorithm is generated in the Arduino and the letters are drawn.

A Comparative Study of Ant and Genetic Algorithms in Digital Mammography

2018 ◽  
pp. 194-200
Author(s):  
J. Magelin Mary ◽  
Chitra K. ◽  
Y. Arockia Suganthi
Keyword(s):  
Genetic Algorithm ◽  
Image Processing ◽  
Medical Image ◽  
Medical Image Processing ◽  
Processing Technique ◽  
Input Image ◽  
Image Processing Technique ◽  
Computational Time ◽  
Image Mining ◽  
The Individual

Image processing technique in general, involves the application of signal processing on the input image for isolating the individual color plane of an image. It plays an important role in the image analysis and computer version. This paper compares the efficiency of two approaches in the area of finding breast cancer in medical image processing. The fundamental target is to apply an image mining in the area of medical image handling utilizing grouping guideline created by genetic algorithm. The parameter using extracted border, the border pixels are considered as population strings to genetic algorithm and Ant Colony Optimization, to find out the optimum value from the border pixels. We likewise look at cost of ACO and GA also, endeavors to discover which one gives the better solution to identify an affected area in medical image based on computational time.

scholarly journals Preliminary Analysis of a Lightweight and Deployable Soft Robot for Space Applications

2021 ◽  
Vol 11 (6) ◽  
pp. 2558
Author(s):  
Mario Troise ◽  
Matteo Gaidano ◽  
Pierpaolo Palmieri ◽  
Stefano Mauro
Keyword(s):  
Preliminary Analysis ◽  
Inverse Kinematics ◽  
Control Algorithm ◽  
Dynamic Models ◽  
Robotic Systems ◽  
Inflation Pressure ◽  
Space Applications ◽  
Space Industry ◽  
Rigid Body Model ◽  
Soft Manipulator

The rising interest in soft robotics, combined to the increasing applications in the space industry, leads to the development of novel lightweight and deployable robotic systems, that could be easily contained in a relatively small package to be deployed when required. The main challenges for soft robotic systems are the low force exertion and the control complexity. In this manuscript, a soft manipulator concept, having inflatable links, is introduced to face these issues. A prototype of the inflatable link is manufactured and statically characterized using a pseudo-rigid body model on varying inflation pressure. Moreover, the full robot model and algorithms for the load and pose estimation are presented. Finally, a control strategy, using inverse kinematics and an elastostatic approach, is developed. Experimental results provide input data for the control algorithm, and its validity domain is discussed on the basis of a simulation model. This preliminary analysis puts the basis of future advancements in building the robot prototype and developing dynamic models and robust control.

scholarly journals Lung Cancer Detection using Convolutional Neural Network

2019 ◽  
Vol 8 (6) ◽  
pp. 3256-3262 ◽  
Keyword(s):  
Lung Cancer ◽  
Image Processing ◽  
Detection System ◽  
Histogram Equalization ◽  
Input Image ◽  
Machine Learning Algorithms ◽  
Morphological Operations ◽  
Image Processing Techniques ◽  
Cad System ◽  
Processing Techniques

The mortality rate is increasing among the growing population and one of the leading causes is lung cancer. Early diagnosis is required to decrease the number of deaths and increase the survival rate of lung cancer patients. With the advancements in the medical field and its technologies CAD system has played a significant role to detect the early symptoms in the patients which cannot be carried out manually without any error in it. CAD is detection system which has combined the machine learning algorithms with image processing using computer vision. In this research a novel approach to CAD system is presented to detect lung cancer using image processing techniques and classifying the detected nodules by CNN approach. The proposed method has taken CT scan image as input image and different image processing techniques such as histogram equalization, segmentation, morphological operations and feature extraction have been performed on it. A CNN based classifier is trained to classify the nodules as cancerous or non-cancerous. The performance of the system is evaluated in the terms of sensitivity, specificity and accuracy

scholarly journals PENERAPAN CITRA TERKOMPRESI PADA SEGMENTASI CITRA MENGGUNAKAN ALGORITMA K-MEANS

2018 ◽  
Vol 2 (1) ◽  
pp. 65-74
Author(s):  
Angga Wijaya Kusuma ◽  
Rossy Lydia Ellyana
Keyword(s):  
Image Processing ◽  
Image Segmentation ◽  
Medical Image ◽  
Performance Test ◽  
Input Image ◽  
Magnetic Resonance Imaging Image ◽  
Resonance Imaging ◽  
Compression Process ◽  
Mri Brain ◽  
Mri Image

In the development of an image not only as a documentation of events. One area that requires image processing is in the field of medicine is radiology. In radiology there is a medical image required by doctors and researchers to be processed for patient analysis. One of the important problems in image processing and pattern recognition is image segmentation into homogeneous areas. Segmentation in medical images will result in a medical image with area boundaries that are important information for analysis. This research applies k-means algorithm to MRI (Magnetic Resonance Imaging) image segmentation. The input image used is the image of MRI (brain and breast) has gone through the compression stage. This compression process is done with the aim of reducing memory usage but the critical information content of MRI image is still maintained. The image of the segmentation result is evaluated through performance test using GCE, VOI, MSE, and PSNR parameters.

scholarly journals Modeling the Kinematics of Two Robots with Denavit–Hartenberg Notation

2020 ◽  
Vol 44 (4) ◽  
pp. 121-128
Author(s):  
Andrzej Burghardt ◽  
Wincenty Skwarek
Keyword(s):  
Mobile Robots ◽  
Inverse Kinematics ◽  
Wheeled Mobile Robots ◽  
Matlab Simulink ◽  
Kinematics Model

AbstractThis article presents a description and methodology for building a kinematics model for the formation of two-wheeled mobile robots transporting a beam using Denavit–Hartenberg notation. The simple and inverse kinematics tasks of this formation were solved. Solutions of kinematics tasks are presented in junction coordinates and global coordinates. The obtained results were simulated using the Matlab–Simulink package together with animation of the solution using a programmed emulator of robot work.

scholarly journals A Review on Deep Image Contrast Enhancement

2020 ◽  
Vol 6 (1) ◽  
pp. 4
Author(s):  
Puspad Kumar Sharma ◽  
Nitesh Gupta ◽  
Anurag Shrivastava
Keyword(s):  
Image Processing ◽  
Deep Learning ◽  
Image Enhancement ◽  
Research Work ◽  
Atmospheric Condition ◽  
Input Image ◽  
Learning Approaches ◽  
Sensing Applications ◽  
Image Contrast Enhancement

In image processing applications, one of the main preprocessing phases is image enhancement that is used to produce high quality image or enhanced image than the original input image. These enhanced images can be used in many applications such as remote sensing applications, geo-satellite images, etc. The quality of an image is affected due to several conditions such as by poor illumination, atmospheric condition, wrong lens aperture setting of the camera, noise, etc [2]. So, such degraded/low exposure images are needed to be enhanced by increasing the brightness as well as its contrast and this can be possible by the method of image enhancement. In this research work different image enhancement techniques are discussed and reviewed with their results. The aim of this study is to determine the application of deep learning approaches that have been used for image enhancement. Deep learning is a machine learning approach which is currently revolutionizing a number of disciplines including image processing and computer vision. This paper will attempt to apply deep learning to image filtering, specifically low-light image enhancement. The review given in this paper is quite efficient for future researchers to overcome problems that helps in designing efficient algorithm which enhances quality of the image.

Inverse Kinematics Modelling and Simulation for Upper Case Writing Robot Control Using ANFIS

2016 ◽  
Vol 836 ◽  
pp. 37-41 ◽  
Author(s):  
Adlina Taufik Syamlan ◽  
Bambang Pramujati ◽  
Hendro Nurhadi
Keyword(s):  
Image Processing ◽  
Character Recognition ◽  
Inverse Kinematics ◽  
Robot Control ◽  
Industrial Revolution ◽  
Training Data ◽  
Robotic Arm ◽  
End Effector ◽  
Precision And Accuracy ◽  
Case Writing

Robotics has lots of use in the industrial world and has lots of development since the industrial revolution, due to its qualities of high precision and accuracy. This paper is designed to display the qualities in a form of a writing robot. The aim of this study is to construct the system based on data gathered and to develop the control system based on the model. There are four aspects studied for this project, namely image processing, character recognition, image properties extraction and inverse kinematics. This paper served as discussion in modelling the robotic arm used for writing robot and generating theta for end effector position. Training data are generated through meshgrid, which is the fed through anfis.

Design and Development of a Fused Vision Force Controller for Nanofiber Grasping and Manipulation

2007 ◽  
Author(s):  
Reza Saeidpourazar ◽  
Nader Jalili
Keyword(s):  
Inverse Kinematics ◽  
Force Feedback ◽  
Atomic Scale ◽  
Design And Development ◽  
Robust Controller ◽  
Grasping And Manipulation ◽  
Performance Capability ◽  
Fabric Production ◽  
Perturbation Estimation ◽  
Vision Feedback

This paper presents the design and development of a fused vision force feedback robust controller for a nanomanipulator used in nanofiber grasping and nano-fabric production applications. The RRP (Revolute Revolute Prismatic) manipulator considered here utilizes two rotational motors with 0.1 μrad resolution and one linear Nanomotor® with 0.25 nm resolution. Weighing just about 30g and having short lever arms (<5cm), the manipulator is capable of achieving well-behaved kinematic characteristics without the backlash in addition to atomic scale precision to guarantee accurate manipulation at the nanoscale. A mathematical model of the nanomanipulator is formulated and both direct and inverse kinematics of the system as well as dynamic equations are presented. A fused force vision feedback based modified optimal robust controller with perturbation estimation for nanomanipulator positioning is then derived and analyzed extensively. Unlike typical macroscale manipulator models and controllers, the controller development is not trivial here due to nanoscale movement and forces, coupled with unmodeled dynamics, nonlinear structural dynamics and mainly lack of position and velocity feedback in this nanomanipulator. Following the development of the fused force vision robust controller, numerical simulations of the proposed controller are preformed to demonstrate the positioning performance capability in nanofiber grasping applications.

scholarly journals Fuzzy proportional-integral speed control of switched reluctance motor with MATLAB/Simulink and programmable logic controller communication

2019 ◽  
Vol 52 (7-8) ◽  
pp. 1137-1144 ◽  
Author(s):  
Ali Uysal ◽  
Serdar Gokay ◽  
Emel Soylu ◽  
Tuncay Soylu ◽  
Serkan Çaşka
Keyword(s):  
Fuzzy Logic ◽  
Control Algorithm ◽  
Programmable Logic Controller ◽  
Programmable Logic ◽  
Matlab Simulink ◽  
Switched Reluctance ◽  
Proportional Integral ◽  
Reluctance Motor ◽  
Integral Controller ◽  
Proportional Integral Controller

In this study, the auto-tuning proportional-integral controller is used to control the speed of a switched reluctance motor. The control algorithm is executed by the programmable logic controller. The proportional integral gains are determined via fuzzy logic. Fuzzy logic is executed on a separate computer via MATLAB/Simulink software. The data exchange between the programmable logic controller and MATLAB/Simulink is done with object linking embedding/component for the process. The fuzzy proportional integral control algorithm is compared with the conventional proportional integral controller. We reduced the load on the programmable logic controller via executing fuzzy logic in a separate computer and at the same time eliminated the disadvantages of the conventional proportional-integral controller. With the proposed method, the engine reached the reference speed value in a short time and the overshoots were eliminated in variable conditions such as different load and different speed conditions.

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