Computer Processing of an Image

2021 ◽  
pp. 1-22
Author(s):  
Chandra Prabha R. ◽  
Shilpa Hiremath
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Digital Images ◽  
Color Image ◽  
Image Representation ◽  
Computer Processing ◽  
Binary Image ◽  
Grayscale Image ◽  
Under Sampling

In this chapter, the authors have briefed about images, digital images, how the digital images can be processed. Image types like binary image, grayscale image, color image, and indexed image and various image formats are explained. It highlights the various fields where digital image processing can be used. This chapter introduces a variety of concepts related to digital image formation in a human eye. The mechanism of the human visual system is discussed. The authors illustrate the steps of image processing. Explanation on different elements of digital image processing systems like image acquisition, and others are also provided. The components required for capturing and processing the image are discussed. Concepts of image sampling, quantization, image representation are discussed. It portrays the operations of the image during sampling and quantization and the two operations of sampling which is oversampling and under-sampling. Readers can appreciate the key difference between oversampling and under-sampling applied to digital images.

Digital image processing color image scanner

1989 ◽  
Author(s):  
Yamaji ◽  
Yoshino ◽  
Ishitobi ◽  
Araki ◽  
Ikeda ◽  
...  
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Color Image

The Research of the Digital Image-Processing of Colorful Painting

2014 ◽  
Vol 926-930 ◽  
pp. 3709-3712
Author(s):  
Yun Zhan ◽  
Jie Lei
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Digital Images ◽  
Color Space ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Practical Application ◽  
Digital Image Processing Technique ◽  
Basic Concepts

The research of the digital image-processing of colorful painting is mainly to aim at the objective circumstances between the digital image and drawing flat vision distortion. This paper is based on the basic concepts of the digital image-processing technique. It expounds digital images advantage, collect, characteristics, recognition and the choice of the color space, the practical application of the digital image in the painting area in sequence. Through the study, we found computer has powerful ability to analyze management in the colorful painting field.

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.

A Promotion of a Color Morphological Filter

2014 ◽  
Vol 548-549 ◽  
pp. 1064-1067
Author(s):  
Shui Ming He
Keyword(s):  
Image Processing ◽  
Mathematical Morphology ◽  
Digital Image Processing ◽  
Digital Image ◽  
Color Image ◽  
Processing Method ◽  
Color Image Processing ◽  
Morphological Filter ◽  
Morphological Operators ◽  
Gray Image

Mathematical morphology can be seen as a special digital image processing method and theory, which has been widely used in various fields. In this paper, the mathematical morphology is applied to the color image processing. In thespace of color image, I have simply expounded the theories and properties of color morphological changs, and defined its morphological operators. According to the application of omni-directional and multi-angle structuring elements composite morphological filter in gray image, I put forward a kind of color morphological filter with omni-directional and multi-angle structuring elements composite. This algorithm has retained its advantages in gray image, however, remaining some drawbacks. Through the optimization of results based on this algorithm, we finally get the relatively ideal denoising effects.

Determination of the Delamination Percentage of Compacted Bamboo Guadua Using Extended Field Digital Images Processing

2014 ◽  
Vol 600 ◽  
pp. 15-20 ◽  
Author(s):  
Edgar Torres ◽  
Patricia Luna ◽  
Caori Takeuchi
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Digital Images ◽  
Digital Processing ◽  
Extended Field ◽  
Images Processing ◽  
Digital Images Processing ◽  
Delamination Area

The percentages of delamination of Compacted Bamboo Guadua were calculated using digital images processing. Three processes were done in the development of this project: tests of delamination, digital image pre-processing and digital image processing of the images acquired. The test of delamination followed the ASTM 5824. The digital image pre-processing was supported on the acquisition of sequences of images, doing a sweeping of the samples, and finally the digital processing worked in the generation of panoramas with sequences of images acquired from the sample. Additionally, the total area from the sample was measured digitally, the segmentation and the measurement of delamination area were done, finding the ratio between the delamination area and the total area of the sample, and obtaining the value of percentage of delamination per section. Digitally, the obtained values for samples made with fibers obtained from Stick (Varillón), Top (Sobrebasa), Middle (Basa) parts and mixture of them were 16.97%, 9.96%, 5.96% and 8.64% respectively.

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.

scholarly journals Forensic Science Research Summary for Forgery Detection of Digital Images

2020 ◽  
Vol 9 (3) ◽  
pp. 1608-1618
Keyword(s):  
Image Processing ◽  
Forensic Science ◽  
Digital Image Processing ◽  
Digital Image ◽  
Digital Images ◽  
Science Research ◽  
Forensic Sciences ◽  
Forgery Detection ◽  
New Approach ◽  
Scanned Images

An important measure of proof collection, storage, and authentication in forensic sciences, which decide the safety and security of any system documents, which can be either portable document formats or scanned images. To gather evidence, or plan a forensic investigation digital images are secured with different modern methodologies. Digital image analysis includes image recovery and surveillance for image information improvement. The goal of forgery detection is to maximize the extraction of information from manipulated images, particularly noisy and post-processed images. Because digital image processing is becoming popular with many advantages in scientific and engineering applications, the forgery techniques are also growing at a rapid rate. Therefore, the main focus is on different types of forgery detection in digital image processing with the help of all transform techniques and comparing their best results for further improvement in order to generate a new approach for a future forensic science investigation.

An Automatic Microalgal Cells Counting Method

2014 ◽  
Vol 1010-1012 ◽  
pp. 178-181
Author(s):  
Yun Zhao ◽  
De Jian Zheng ◽  
Ying Shen
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Binary Image ◽  
Morphological Operations ◽  
Microscopic Image ◽  
Median Filtering ◽  
Counting Method ◽  
Automatic Counting

An automatic counting method for microalgal cells were proposed using digital image processing with characteristics of microalgae microscopic image considered. Firstly, the microalgae image was pretreated with graying, and was then applied the median filtering to remove the noise. Secondly, the image was applied Bot-hat conversion to enhance the contrast. Thirdly, the image was segmented with Otsu algorithm, and was then applied morphological operations. Finally, the binary image segments representing microalgal cells were labeled and counted. The results of experiments showed that this method was simple, efficient and accurate in counting microalgal cells in the microscopic image.

Digital Image Processing

2018 ◽  
pp. 9-43
Keyword(s):  
Image Processing ◽  
Quality Improvement ◽  
Image Enhancement ◽  
Digital Image Processing ◽  
Digital Image ◽  
Digital Images ◽  
Visual Quality ◽  
Spatial Filtering ◽  
Digital Image Enhancement ◽  
Java Code

The first two sections of this chapter introduce the motivation and fundamental theoretical perceptions towards DIP and encoding formats. The RGB system color and the visual quality improvement (by increasing the contrast with histograms enhancement techniques) are emphasized in section “Digital Image Enhancement” and “Elementary Operations With Digital Images”, respectively. Spatial filtering and masks are analyzed in section “Filtering”, which some Java code has been included for illustrative purposes. The next section explains how to save a myGeoffice© generated image to your hard disk and provides examples of image processing. Section “JHLABS® Image Editor” and “LightBox® Image Editor” depicts JHLabs®, a Web editor built on Swing technology, and Lightbox® of myGeoffice©. Its filtering capabilities are presented in the last section.

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