Using entropy information measures for edge detection in digital images

2015 ◽  
Author(s):  
Diego Susanj ◽  
Vjeran Tuhtan ◽  
Luka Lenac ◽  
Gordan Gulan ◽  
Ivica Kozar ◽  
...  
Keyword(s):  
Edge Detection ◽  
Digital Images ◽  
Information Measures ◽  
Entropy Information

Segmentation of digital images with various edge detection techniques using OpenCV

2021 ◽  
pp. 535-539
Author(s):  
Saumitra Shukla ◽  
Vaishali Kikan ◽  
Ritvi Sachdeva ◽  
Yash Chaturvedi ◽  
Ronak Jain
Keyword(s):  
Edge Detection ◽  
Digital Images ◽  
Detection Techniques

An Algorithmic Approach Based on CMS Edge Detection Technique for the Processing of Digital Images

2020 ◽  
pp. 252-272
Author(s):  
Kalyan Kumar Jena ◽  
Sasmita Mishra ◽  
Sarojananda Mishra
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Digital Image Processing ◽  
Digital Images ◽  
Color Images ◽  
Experimental Results ◽  
Detection Technique ◽  
Algorithmic Approach ◽  
Current Scenario ◽  
Edge Detection Method

Research in the field of digital image processing (DIP) has increased in the current scenario. Edge detection of digital images is considered as an important area of research in DIP. Detecting edges in different digital images accurately is a challenging work in DIP. Different methods have been introduced by different researchers to detect the edges of images. However, no method works well under all conditions. In this chapter, an edge detection method is proposed to detect the edges of gray scale and color images. This method focuses on the combination of Canny, mathematical morphological, and Sobel (CMS) edge detection operators. The output of the proposed method is produced using matrix laboratory (MATLAB) R2015b and compared with Sobel, Prewitt, Roberts, Laplacian of Gaussian (LoG), Canny, and mathematical morphological edge detection operators. The experimental results show that the proposed method works better as compared to other existing methods in detecting the edges of images.

Boundary Layer Detection Techniques Applied to Edge Detection

2019 ◽  
Vol 19 (02) ◽  
pp. 1950010 ◽  
Author(s):  
Fernando O. Guillén-Reyes ◽  
Francisco J. Domínguez-Mota
Keyword(s):  
Boundary Layer ◽  
High Resolution ◽  
Edge Detection ◽  
Digital Image ◽  
Execution Time ◽  
Digital Images ◽  
Intensity Function ◽  
Detection Techniques ◽  
Novel Algorithm

In this paper, we describe a novel algorithm for edge detection on a digital image, which is based locally on the directional averaged gradient properties of the intensity function, and produces very satisfactory results in high-resolution digital images in low execution time. Several examples show results which are comparable to those obtained by Canny and Sobel methods.

scholarly journals Digital Watermarking using Multiscale Ridgelet Transform

2013 ◽  
pp. 162-167
Author(s):  
Manmit Kaur ◽  
H. P. Sinha
Keyword(s):  
Wavelet Transform ◽  
Image Compression ◽  
Edge Detection ◽  
Discrete Cosine Transform ◽  
Digital Watermarking ◽  
High Frequency ◽  
Digital Images ◽  
Experimental Results ◽  
Ridgelet Transform ◽  
Frequency Bands

The multi-resolution watermarking method for digital images proposed in this work. The multiscale ridgelet coefficients of low and high frequency bands of the watermark is embedded to the most significant coefficients at low and high frequency bands of the multiscale ridgelet of an host image, respectively. A multi-resolution nature of multiscale ridgelet transform is exploiting in the process of edge detection. Experimental results of the proposed watermarking method are compared with the previously available watermarking algorithm wavelet transform. Moreover, the proposed watermarking method also tested on images attached by Discrete Cosine Transform (DCT) and wavelet based lossy image compression techniques.

scholarly journals PENERAPAN METODE PREWITT, CANNY DAN SOBEL PADA PROSES DETEKSI TEPI CITRA

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Polinus Laia
Keyword(s):  
Object Recognition ◽  
Edge Detection ◽  
Digital Images ◽  
Boundary Line ◽  
Initial Information ◽  
Identification Process

Edge detection is the first step to completing information in an image where the edges characterize object boundaries that are useful for the identification process. There are many methods of edge detection, but in this study, the methods taken are the Prewitt method, the CANNY method and the Sobel method to detect the edges of objects in digital images. This system applies all three methods to improve the appearance of the boundary line of an object. This study discusses how to apply the three methods in the application Matlab 7.1. The purpose and benefits of this application are to recognize the application of the results of edge detection and obtain initial information about the edge detection features for object recognition for future researchers.

scholarly journals The Segmentation of Neutron Digital Radiography Image through the Edge Detection Method

2020 ◽  
Vol 10 (1) ◽  
pp. 11
Author(s):  
Ayu Fitri Amalia ◽  
Widodo Budhi
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Digital Image Processing ◽  
Neutron Beam ◽  
Digital Radiography ◽  
Digital Image ◽  
Digital Images ◽  
Neutron Radiography ◽  
Detection Methods

The digital image processing is one way to manipulate one or more digital images. Image segmentation has an essential role in the field of image analysis. The aim of this study was to develop an application to perform digital image processing of neutron digital radiographic images, hoping to improve the image quality of the digital images produced. The quality of edge detection could be used for the introduction of neutron digital radiographic image patterns through artificial intelligence. Interaction of neutrons with the matter mainly by nuclear reaction, elastic, and inelastic scattering. A neutron can quickly enter into a nucleus of an atom and cause a reaction. It is because a neutron has no charge. Neutrons can be used for digital imaging due to high-resolution information from deep layers of the material. The attenuated neutron beam in neutron radiography are passing through the investigated object. The object in a uniform neutron beam is irradiated to obtain an image neutron. The technique used in segmenting the neutron radiography in this study was a digital technique using a camera with a charge-coupled device (CCD), which was deemed more efficient technique compared to the conventional one. Through this technique, images could be displayed directly on the monitor without going through the film washing process. Edge detection methods were implemented in the algorithm program. It was the first step to complement the image information where edges characterize object boundaries. It is useful for the process of segmenting and identifying objects in neutron digital radiography images. The edge detection methods used in this study were Sobel, Prewitt, Canny, and Laplacian of Gaussian. According to the results of the image that have been tested for edge detection, the best image was carried out by the Canny operator because the method is more explicit. The obtained edges were more connected than the other methods which are still broken. The Canny technique provided edge gradient orientation which resulted in a proper localization.

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