scholarly journals Application of Digital Image Based on Machine Learning in Media Art Design

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Ciguli Wu
Keyword(s):  
Digital Image ◽  
Motion Compensation ◽  
Digital Images ◽  
Reference Image ◽  
Media Art ◽  
Regression Problem ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Art Design ◽  
Pixel Interpolation

In digital media art, expressive force is an important art form of media. This paper studies digital images that have the same effect when applied to media art. The research object is media art images, and the application effect of the proposed algorithm is related to the media art images. The development of digital image technology has brought revolutionary changes to traditional media art expression techniques. In this paper, a partial-pixel interpolation technique based on convolutional neural network is proposed. Supervised training of convolutional neural networks requires predetermining the input and target output of the network, namely, integer image and fractional image in this paper. To solve the problem that the subpixel sample cannot be obtained, this paper first analyzes the imaging principle of digital image and proposes a subpixel sample generation algorithm based on Gaussian low-pass filter and polyphase sampling. From the perspective of rate distortion optimization, the purpose of pixel motion compensation is to improve the accuracy of interframe prediction. Therefore, this paper defines pixel motion compensation as an interframe regression problem, that is, the mapping process of the reference image integral pixel sample to the current image sample to be encoded. In this paper, a generalized partial-pixel interpolation model is proposed for bidirectional prediction. The partial-pixel interpolation of bidirectional prediction is regarded as a binary regression model; that is, the integral pixel reference block in two directions is mapped to the current block to be coded. It further studies how to apply the trained digital images to media art design more flexibly and efficiently.

Analysis on Adjusting Effect and Spectral Characteristics of Digital Image Sampling

2014 ◽  
Vol 539 ◽  
pp. 471-474
Author(s):  
Hai Ying Liu
Keyword(s):  
Digital Image ◽  
Hot Spot ◽  
Modern Art ◽  
Spectral Characteristics ◽  
Image Process ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Image Sampling ◽  
Low Pass ◽  
Continuous Tone

When it comes to the digitized image, it is a process of converting analog image of continuous tone which has been sampled and quantized into digital image. The application of digital technology in modern art has become one of the hot spot in this field. First of all, this paper undertakes the digital image process of image. According to the filtering properties of the Dirac function, this paper analyzes the two-dimensional sampling principle of digital image. Based on this, the relationship between image spectrum before sampling and after sampling is compared and analyzed according to the related properties of Fourier transform. And then it is obtained that it is concluded that the ideal low-pass filter can make the sample undistorted. By further analyzing the error of the sampling value quantification processing, the rebuilt best quantitative values of image can be obtained. Thats to say, the reconstruction of digital image is the inverse process of image sampling. To a certain extent, it provides scientific theoretical basis for the integration of digital image in modern art design.

Reproducibility of Immunostaining Quantification and Description of a New Digital Image Processing Procedure for Quantitative Evaluation of Immunohistochemistry in Pathology

2009 ◽  
Vol 15 (4) ◽  
pp. 353-365 ◽  
Author(s):  
Vagner Bernardo ◽  
Simone Q.C. Lourenço ◽  
Renato Cruz ◽  
Luiz H. Monteiro-Leal ◽  
Licínio E. Silva ◽  
...  
Keyword(s):  
Image Processing ◽  
Quantitative Evaluation ◽  
Digital Image ◽  
Visual Observation ◽  
Human Vision ◽  
Intraobserver Variability ◽  
Image Subtraction ◽  
Specific Staining ◽  
Pass Filter ◽  
Low Pass Filter

AbstractQuantification of immunostaining is a widely used technique in pathology. Nonetheless, techniques that rely on human vision are prone to inter- and intraobserver variability, and they are tedious and time consuming. Digital image analysis (DIA), now available in a variety of platforms, improves quantification performance: however, the stability of these different DIA systems is largely unknown. Here, we describe a method to measure the reproducibility of DIA systems. In addition, we describe a new image-processing strategy for quantitative evaluation of immunostained tissue sections using DAB/hematoxylin-stained slides. This approach is based on image subtraction, using a blue low pass filter in the optical train, followed by digital contrast and brightness enhancement. Results showed that our DIA system yields stable counts, and that this method can be used to evaluate the performance of DIA systems. The new image-processing approach creates an image that aids both human visual observation and DIA systems in assessing immunostained slides, delivers a quantitative performance similar to that of bright field imaging, gives thresholds with smaller ranges, and allows the segmentation of strongly immunostained areas, all resulting in a higher probability of representing specific staining. We believe that our approach offers important advantages to immunostaining quantification in pathology.

scholarly journals Digital Image Filtering Optimization Supporting Iberian Ham Quality Prediction

Foods ◽  
2019 ◽  
Vol 9 (1) ◽  
pp. 25
Author(s):  
Francisco Perán-Sánchez ◽  
Salud Serrano ◽  
Eduardo Gutiérrez de Ravé ◽  
Elena Sánchez-López ◽  
Ana Cumplido ◽  
...  
Keyword(s):  
Digital Image ◽  
Multifractal Analysis ◽  
Digital Images ◽  
Fractal Dimensions ◽  
Image Filtering ◽  
Quality Prediction ◽  
Pass Filter ◽  
High Pass Filter ◽  
High Pass

Digital images of food for later analysis tend to be heterogeneous in terms of color and luminosity. Improving these images by using filters is necessary and crucial before further processing. This paper compares the non-use of filters and the use of high-pass filters in the images of hand-cut Iberian ham that will be used in a multifractal analysis for the study of fat and its infiltration. The yielded results show that with the use of a high-pass filter, more accurate fractal dimensions were obtained, which can be featured in predictive techniques of Iberian ham quality.

Authentication of Digital Image using Exif Metadata and Decoding Properties

2018 ◽  
pp. 335-341 ◽  
Author(s):  
D. P. Gangwar ◽  
Anju Pathania
Keyword(s):  
Digital Image ◽  
Digital Images ◽  
Software Tools ◽  
Robust Analysis

This work presents a robust analysis of digital images to detect the modifications/ morphing/ editing signs by using the image’s exif metadata, thumbnail, camera traces, image markers, Huffman codec and Markers, Compression signatures etc. properties. The details of the whole methodology and findings are described in the present work. The main advantage of the methodology is that the whole analysis has been done by using software/tools which are easily available in open sources.

Design of Programmable Wideband Low Pass Filter with Continuous-Time/Discrete-Time Hybrid Architecture

2017 ◽  
Vol E100.C (10) ◽  
pp. 858-865 ◽  
Author(s):  
Yohei MORISHITA ◽  
Koichi MIZUNO ◽  
Junji SATO ◽  
Koji TAKINAMI ◽  
Kazuaki TAKAHASHI
Keyword(s):  
Discrete Time ◽  
Continuous Time ◽  
Hybrid Architecture ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Low Pass

Development of New Image Registration Techniques – A Research Framework

2018 ◽  
Vol 8 (3) ◽  
pp. 50
Author(s):  
Sindhu Madhuri G. ◽  
Indira Gandhi M P
Keyword(s):  
Image Processing ◽  
Image Registration ◽  
Digital Image Processing ◽  
Digital Image ◽  
Creative Thinking ◽  
Reference Image ◽  
Transformation Technique ◽  
Research Framework ◽  
Registration Process ◽  
Data Source

Image is a basic and fundamental data source for the digital image processing. This image data source is required to be processed into information or intelligence and further to knowledge levels where it is required to understand and migrate into knowledge economy systems. Image registration is one of such key and most important process already identified in the digital image processing domain. Image registration is a process of bringing the reference image and sensed image into a common co-ordinate system, and application of complex transformation techniques for necessary comparison of reference with sensed images obtained from different - views, times, spaces, etc., in order to extract the valuable information and intelligence embedded in them. Due to the complexity of overall image registration process, it is difficult to suggest a single transformation technique even for a specific application. In addition, it is highly impossible to suggest one single transformation technique for comparison of various sensed images with a reference image during the image registration process. This research gap calls for the development of new image registration techniques for the application of more than one transformation technique during the image registration process for the necessary comparisons with reference image & sensed images, those are obtained from the available heterogeneous sources or sensors, based on the requirement. In addition, it is a basic need to attempt for the measurement of effectiveness of the image registration process also. Therefore, a research framework is developed for image registration process and attempted for the measurement of its effectiveness also. This new research area is a novel idea, and is expected to emerge as a provision for the knowledge computations with creative thinking through the embedded intelligence extraction during the complex image registration process.

ANALYSIS AND IMPROVEMENT TECHNIQUES FOR THE TRANSFER FUNCTION OF A PLANAR LOW - PASS FILTER

2016 ◽  
Vol 15 (12) ◽  
pp. 2579-2586
Author(s):  
Adina Racasan ◽  
Calin Munteanu ◽  
Vasile Topa ◽  
Claudia Pacurar ◽  
Claudia Hebedean
Keyword(s):  
Transfer Function ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Low Pass

PERBANDINGAN METODE MD4 DAN SHA 384 UNTUK MENDETEKSI ORISINALITAS CITRA DIGITAL

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Lemcia Hutajulu ◽  
Hery Sunandar ◽  
Imam Saputra
Keyword(s):  
Digital Image ◽  
Detrimental Effect ◽  
Digital Images ◽  
Computer Crime ◽  
The Other ◽  
Image Manipulation ◽  
The Internet ◽  
Secret Key

Cryptography is used to protect the contents of information from anyone except those who have the authority or secret key to open information that has been encoded. Along with the development of technology and computers, the increase in computer crime has also increased, especially in image manipulation. There are many ways that people use to manipulate images that have a detrimental effect on others. The originality of a digital image is the authenticity of the image in terms of colors, shapes, objects and information without the slightest change from the other party. Nowadays many digital images circulating on the internet have been manipulated and even images have been used for material fraud in the competition, so we need a method that can detect the image is genuine or fake. In this study, the authors used the MD4 and SHA-384 methods to detect the originality of digital images, by using this method an image of doubtful authenticity can be found out that the image is authentic or fake.Keywords: Originality, Image, MD4 and SHA-384

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