scholarly journals Algorithmic Approaches For Image Edge Detection

2021 ◽  
Vol 10 (3) ◽  
pp. 1942-1948
Keyword(s):  
Image Processing ◽  
Image Segmentation ◽  
Edge Detection ◽  
Image Enhancement ◽  
Digital Image Processing ◽  
Digital Image ◽  
Image Edge Detection ◽  
Image Edge ◽  
Algorithmic Approaches

Edge detection is most important technique in digital image processing. It play an important role in image segmentation and many other applications. Edge detection providesfoundation to many medical and military applications.It difficult to generate a generic code for edge detection so many kinds ofalgorithms are available. In this article 4 different approaches Global image enhancement with addition (GIEA), Global image enhancement with Multiplication (GIEM),Without Global image enhancement with Addition (WOGIEA),and without Global image enhancement with Multiplication (WOGIEM)for edge detection is proposed. These algorithms are validatedon 9 different images. The results showthat GIEA give us more accurate results as compare to other techniques.

scholarly journals DIGITAL IMAGE PROCESSING MENGGUNAKAN PERANGKAT LUNAK NI VISION DAN IP KAMERA DENGAN ROVER BOGIE ROBOT

2019 ◽  
Vol 6 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Arif Ainur Rafiq ◽  
Muhamad Yusuf ◽  
Pujono Pujono
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Mobile Phone ◽  
Digital Image Processing ◽  
Digital Image ◽  
Image Edge Detection ◽  
Ip Camera ◽  
Image Edge

Penjelajahan lapangan sering diperlukan untuk tujuan penelitian ataupun dokumentasi. Berbagai macam resiko diabaikan demi tereksplorasinya suatu tempat. Serangan binatang buas dan cuaca ekstrim menjadi contoh bahaya yang dapat menimbulkan resiko apabila penjelajahan melibatkan manusia secara langsung. Medan yang sulit juga dapat menghambat penelitian serta pengambilan dokumentasi. Untuk mengatasi permasalahan di atas dibuatlah Rover Bogie Robot. Pada robot terpasang kamera guna memudahkan penelitian dan dokumentasi. Robot yang didesain berupa robot penjelajah dengan suspensi passive rocker bogie. Robot penjelajah ini bisa melalui berbagai medan dengan karakteristik yang berbeda. Gambar dokumentasi akan diolah pada Digital Image Processing yang akan mempermudah observasi. Mikrokontroller yang digunakan pada robot ini yaitu Arduino Mega. Kamera yang digunakan adalah IP Camera pada mobile phone dengan menggunakan aplikasi IP Webcam dan Configure IP Adapter serta LabVIEW Vision sebagai GUI (Graphical Unit Interface) dan kontrol pengambilan gambar. Sebagai pengendali, digunakan wireless joystick. Digital Image Processing yang digunakan yaitu Extract Single Color, Threshold Image, Edge Detection dan RGB Gain. Berdasarkan pengujian, pengolahan gambar menggunakan Digital Image Processing dapat bekerja sesuai dengan yang diharapkan. Robot dapat melewati berbagai karakterisitik medan yaitu bebatuan ringan, berumput rendah, medan dengan permukaan tidak rata dan naik dengan ketinggian maksimal 5 cm. Pengujian kontrol menggunakan wireless joystick dapat dilakukan dengan jarak maksimal 11 meter. Secara keseluruhan, Rover Bogie Robot dapat digunakan sebagai media untuk penjelajahan yang bertujuan untuk penelitian dan dokumentasi pada medan dengan karakteristik yang berbeda menggunakan kontrol wireless joystick. 

A Study on Different Edge Detection Techniques in Digital Image Processing

2017 ◽  
pp. 100-122 ◽  
Author(s):  
Shouvik Chakraborty ◽  
Mousomi Roy ◽  
Sirshendu Hore
Keyword(s):  
Image Processing ◽  
Image Segmentation ◽  
Edge Detection ◽  
Digital Image Processing ◽  
Digital Image ◽  
Basic Feature ◽  
Detection Methods ◽  
Natural Image ◽  
Detection Techniques ◽  
Image Edges

Image segmentation is one of the fundamental problems in image processing. In digital image processing, there are many image segmentation techniques. One of the most important techniques is Edge detection techniques for natural image segmentation. Edge is a one of the basic feature of an image. Edge detection can be used as a fundamental tool for image segmentation. Edge detection methods transform original images into edge images benefits from the changes of grey tones in the image. The image edges include a good number of rich information that is very significant for obtaining the image characteristic by object recognition and analyzing the image. In a gray scale image, the edge is a local feature that, within a neighborhood, separates two regions, in each of which the gray level is more or less uniform with different values on the two sides of the edge. In this paper, the main objective is to study the theory of edge detection for image segmentation using various computing approaches.

scholarly journals Comparison of Adaptive Ant Colony Optimization for Image Edge Detection of Leaves Bone Structure

2018 ◽  
Vol 6 (2) ◽  
pp. 328-336 ◽  
Author(s):  
Febri Liantoni ◽  
Rifki Indra Perwira ◽  
Daniel Silli Bataona
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Ant Colony Optimization ◽  
Digital Image Processing ◽  
Optimization Algorithm ◽  
Bone Structure ◽  
Ant Colony ◽  
Ant Colony Optimization Algorithm ◽  
Image Edge Detection ◽  
Image Edge

Leaf bone structure has a characteristic that can be used as a reference in digital image processing. One form of digital image processing is image edge detection. Edge detection is the process of extracting edge information from an image. In this research, Adaptive Ant Colony Optimization algorithm is proposed for edge image detection of leaf bone structure. The Adaptive Ant Colony Optimization method is a modification of Ant Colony Optimization, in which the initial an ant dissemination process is no longer random, but it is done by a pixel placement process that allows for an edge based on the value of the image gradient. As a comparison also performed edge detection using Robert and Sobel method. Based on the experiments performed, Adaptive Ant Colony Optimization algorithm is capable of producing more detailed image edge detection and has thicker borders than others. Keywords: edge detection, ant colony optimization, robert, sobel

Study of Various Image Segmentation Methodologies

2017 ◽  
pp. 1-27
Author(s):  
Abahan Sarkar ◽  
Ram Kumar
Keyword(s):  
Image Processing ◽  
Image Segmentation ◽  
Edge Detection ◽  
Digital Image Processing ◽  
Digital Image ◽  
New Technologies ◽  
Region Of Interest ◽  
Literature Survey ◽  
Segmentation Algorithms ◽  
Segmentation Image

In day-to-day life, new technologies are emerging in the field of Image processing, especially in the domain of segmentation. Image segmentation is the most important part in digital image processing. Segmentation is nothing but a portion of any image and object. In image segmentation, the digital image is divided into multiple set of pixels. Image segmentation is generally required to cut out region of interest (ROI) from an image. Currently there are many different algorithms available for image segmentation. This chapter presents a brief outline of some of the most common segmentation techniques (e.g. Segmentation based on thresholding, Model based segmentation, Segmentation based on edge detection, Segmentation based on clustering, etc.,) mentioning its advantages as well as the drawbacks. The Matlab simulated results of different available image segmentation techniques are also given for better understanding of image segmentation. Simply, different image segmentation algorithms with their prospects are reviewed in this chapter to reduce the time of literature survey of the future researchers.

Design and Implementation of Digital Image Processing Teaching Demonstration System

2013 ◽  
Vol 347-350 ◽  
pp. 3237-3241
Author(s):  
Shi Min Zhang
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Color Image ◽  
Color Image Processing ◽  
Practical Application ◽  
Image Transformation ◽  
Design And Implementation ◽  
Image Edge Detection ◽  
Image Edge

Digital image processing technology is widely used in the further application of computer graphics. This thesis introduces a digital image processing teaching demonstration system including image file management, image transformation, color image processing, binarization, image enhancement, and image edge detection extra. In function, it embraces basic skills in digital image processing. This thesis is a favorable assistant in your study and practical application by means of friendly operation interface, the contrast of image processing effect demonstration and algorithm routine.

A Study on Different Edge Detection Techniques in Digital Image Processing

2018 ◽  
pp. 1686-1708 ◽  
Author(s):  
Shouvik Chakraborty ◽  
Mousomi Roy ◽  
Sirshendu Hore
Keyword(s):  
Image Processing ◽  
Image Segmentation ◽  
Edge Detection ◽  
Digital Image Processing ◽  
Digital Image ◽  
Basic Feature ◽  
Detection Methods ◽  
Natural Image ◽  
Detection Techniques ◽  
Image Edges

Image segmentation is one of the fundamental problems in image processing. In digital image processing, there are many image segmentation techniques. One of the most important techniques is Edge detection techniques for natural image segmentation. Edge is a one of the basic feature of an image. Edge detection can be used as a fundamental tool for image segmentation. Edge detection methods transform original images into edge images benefits from the changes of grey tones in the image. The image edges include a good number of rich information that is very significant for obtaining the image characteristic by object recognition and analyzing the image. In a gray scale image, the edge is a local feature that, within a neighborhood, separates two regions, in each of which the gray level is more or less uniform with different values on the two sides of the edge. In this paper, the main objective is to study the theory of edge detection for image segmentation using various computing approaches.

MATLAB-Based Digital Image Processing Technology Research

2014 ◽  
Vol 687-691 ◽  
pp. 3769-3772 ◽  
Author(s):  
Chung Yang Shi
Keyword(s):  
Image Processing ◽  
Image Segmentation ◽  
Image Enhancement ◽  
Digital Image Processing ◽  
Digital Image ◽  
Processing Technology ◽  
Future Research ◽  
Technology Research ◽  
Image Processing Technology ◽  
The Future

This paper is an application of digital image processing technology based on MATLAB; this paper introduces the MATLAB image enhancement and image segmentation technology, in order to lay a foundation for the future research and application.

Cellular Automata Algorithms for Digital Image Processing

Biometrics ◽  
2017 ◽  
pp. 382-402
Author(s):  
Petre Anghelescu
Keyword(s):  
Image Processing ◽  
Cellular Automata ◽  
Edge Detection ◽  
Digital Image Processing ◽  
Digital Image ◽  
Image Understanding ◽  
Software Application ◽  
Detection Algorithms ◽  
Human Image ◽  
The Impact

In this paper are presented solutions to develop algorithms for digital image processing focusing particularly on edge detection. Edge detection is one of the most important phases used in computer vision and image processing applications and also in human image understanding. In this chapter, implementation of classical edge detection algorithms it is presented and also implementation of algorithms based on the theory of Cellular Automata (CA). This work is totally related to the idea of understanding the impact of the inherently local information processing of CA on their ability to perform a managed computation at the global level. If a suitable encoding of a digital image is used, in some cases, it is possible to achieve better results in comparison with the solutions obtained by means of conventional approaches. The software application which is able to process images in order to detect edges using both conventional algorithms and CA based ones is written in C# programming language and experimental results are presented for images with different sizes and backgrounds.

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