scholarly journals RANCANG BANGUN APLIKASI DETEKSI TEPI CITRA DIGITAL MENGGUNAKAN ALGORITMA PREWITT

2021 ◽  
Vol 4 (1) ◽  
pp. 83-87
Author(s):  
Ardiansyah Putra ◽  
◽  
Volvo Sihombing ◽  
Mustafha Haris Munandar ◽  
◽  
...  
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Digital Image Processing ◽  
Digital Image ◽  
Human Vision ◽  
Processing Technology ◽  
Image Information ◽  
Human Eye ◽  
Image Object ◽  
Boundary Lines

Edge detection is one of the algorithms used in Digital Image Processing. This algorithm serves to identify the line/edge of the image object to highlight the boundary lines of the image information. Edge is a set of connected pixels (connected pixels) that restricts the objects contained in the image. Senses the eye is one that is used by humans to see.However, the human eye has its limitations in capturing the electromagnetic signals.Therefore, created a computer or imaging machine that can capture almost the entire signal elektromagnetic. Imaging machines can work with imagery from sources that do not fit, do not fit or can not be captured by human vision. This is why digital image processing have very wide usefulness. Image processing technology can fit into a variety of fields such as medicine, geology, marine , industrial and others.Keywords:Image,Prewitt,Edge,Java,Netbeans

Measurement Technology Research on Target and Projectiles’ Miss Distance Based on Digital Image Processing

2011 ◽  
Vol 383-390 ◽  
pp. 4987-4993
Author(s):  
Zhi Qiang Ma ◽  
Shi Yu Sun ◽  
Yuan Zeng Cheng ◽  
Chun Ping Wang
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Digital Image Processing ◽  
Digital Image ◽  
Template Matching ◽  
Distance Measurement ◽  
Processing Technology ◽  
Measurement Technology ◽  
Image Processing Technology ◽  
Miss Distance

At the closed-loop calibration research of anti-aircraft weapons systems, the miss distance between target and projectiles is difficult to obtain accurately. In order to solve this problem, this paper provided using the digital image processing technology to research the miss distance measurement methods, focusing on the image filtering technology, edge detection technology and target recognition technology. According to the simulation results, the paper selected the adaptive median filtering to remove image noise, adopted the edge detection method based on the iterative threshold to obtain target edge and used template matching technology to identify the target in the image. Finally, according to the principle of image measurement technique, using centroid tracking measurement technology to achieve the miss distance measurement. The application of digital image processing technology makes the miss distance measurement become simple, effective and convenient. This measurement method enables to save money, improve accuracy, get results in real time and have a high research value.

Preliminary research on a method of outcrops extraction on Karst Gabin ecosystem based on digital image processing: the case of the Mengzi Gabin basin

2021 ◽  
Author(s):  
Zhe Yin ◽  
Zhijie Shan
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Processing Technology ◽  
Rocky Desertification ◽  
Rock Outcrops ◽  
Bare Rock ◽  
Image Processing Technology ◽  
Karst Ecosystem ◽  
Bare Rock Rate

<p>Rock outcrops are common features of the karst ecosystem The bare rock rate is an important indicator for rocky desertification grades classification, and its accurate extraction can benefit for understanding the distribution characteristics of rock outcrops in desertification areas and the classification of rocky desertification grades. In order to explore the distribution pattern of surface bare rocks in the typical geomorphic environment of the Karst gabin basin, the Mengzi gabin basin was carried out as the research site. The combination of UAV shooting images and digital image processing technology were used, the characteristics of bare rock rate on the karst fault basin after vegetation restoration were shaped. Our results showed that digital image processing technology can be used for extraction of bare rock rate in Karst area, and the effective combination of UAV technology and digital image processing technology can quickly obtain bare rock rate data of typical landform in Karst gabin basins. After performing drone aerial photography on 26 typical landform information under different bare rock distribution conditions on the Mengzi gabin basin, the results of the image processing analysis showed that the bare rock rate is between 2.7%-28.9%. The research provide technical support for the assessment of the karst ecosystem degradation and the evaluation of the current status of rocky desertification in karst gabin basin</p>

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.

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.

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