An investigation into colour combination in paintings via graph theory

2019 ◽  
Vol 8 (4) ◽  
Author(s):  
Samaneh Jolany Vangah ◽  
Yousef Jamali ◽  
Mozaffar Jamali
Keyword(s):  
Image Processing ◽  
Graph Theory ◽  
Network Analysis ◽  
Visual Arts ◽  
Digital Image ◽  
Degree Distribution ◽  
Network Science ◽  
Node Centrality ◽  
Classification Of Images

Abstract In visual arts, painting is deeply reliant on the colour combination for its impact, depth and emotion. Recently, many studies have focused on image processing, regarding identification and classification of images, using some colour features such as saturation, hue, luminance and so forth. This study aims to delve into some of the painting styles from the perspective of graph theory and network science. We compared a number of famous paintings to find out the likely pattern that an artist uses for colour combination and juxtaposition. To achieve this aim, the digital image of a painting is converted to a graph where each vertex represents one of the painting’s colours. In this graph, two vertices would be adjacent if and only if the two relative colours could be found in at least two adjacent pixels in the digital image. Among the several tools for network analysis, clustering, node centrality and degree distribution are used. Outcomes showed that artists unconsciously are following subtle mathematical rules to reach harmony and coordination in their work.

scholarly journals Reconhecimento de Padrões em Imagens de Triatomíneos Usando Redes Neurais Artificiais com Algoritmo Backpropagation

2020 ◽  
Author(s):  
Joao Marcelino Pacheco Neto ◽  
Otavio Noura Teixeira
Keyword(s):  
Neural Networks ◽  
Image Processing ◽  
Artificial Neural Networks ◽  
Trypanosoma Cruzi ◽  
Chagas Disease ◽  
Digital Image Processing ◽  
Digital Image ◽  
Human Infection ◽  
Classification Of Images

Chagas disease, also known as American trypanosomiasis isone of the consequences of the human infection caused by theflagellate protozoan called Trypanosoma cruzi transmittedby the barbeiro of the subfamily Triatominae known as triatomines.In the Lower Tocantins region of the state of Para,three genera of barbers transmitting the disease are found.Searching for a way to automate the manual recognition process,this work aimed to implement a Model of Recognitionand Classification of Images of barbers found in the LowerTocantins region in order to recognize the genus of the insectthrough the use of Artificial Neural Networks PerceptronMulti-layered and performing training with Backpropagationalgorithm, helping to identify the transmitters. In themiddle of this recognition, the Digital Image Processing isperformed to extract important characteristics relevant to theclassification. This entire process is performed in MATLABsoftware through scripts and the creation of the ArtificialNeural Network in the toolbox called Pattern RecognitionApp.

Classification of crossed immunoelectrophoretic patterns using digital image processing and artificial neural networks

1992 ◽  
Vol 13 (1) ◽  
pp. 411-415 ◽  
Author(s):  
Ib Søndergaard ◽  
Britta Naimi Krath ◽  
Martin Hagerup
Keyword(s):  
Neural Networks ◽  
Image Processing ◽  
Artificial Neural Networks ◽  
Digital Image Processing ◽  
Digital Image ◽  
Artificial Neural

scholarly journals Techniques for Image Segmentation: A Critical Review

2021 ◽  
Vol 9 (3) ◽  
pp. 1-4
Author(s):  
Harshita Mishra ◽  
Anuradha Misra
Keyword(s):  
Data Mining ◽  
Image Processing ◽  
Image Segmentation ◽  
Digital Image ◽  
Electronic Devices ◽  
Data Mining Technique ◽  
Mining Technique ◽  
Mathematical Algorithms ◽  
Picture Element

In today’s world there is requirement of some techniques or methods that will be helpful for retrieval of the information from the images. Information those are important for finding solution to the problems in the present time are needed. In this review we will study the processing involved in the digitalization of the image. The set or proper array of the pixels that is also called as picture element is known as image. The positioning of these pixels is in matrix which is formed in columns and rows. The image undergoes the process of digitalization by which a digital image is formed. This process of digitalization is called digital image processing of the image (D.I.P). Electronic devices as such computers are used for the processing of the image into digital image. There are various techniques that are used for image segmentation process. In this review we will also try to understand the involvement of data mining for the extraction of the information from the image. The process of the identifying patterns in the large stored data with the help of statistic and mathematical algorithms is data mining. The pixel wise classification of the image segmentation uses data mining technique.

The pluviospectrometer: classification of falling hydrometeors via digital image processing

1994 ◽  
Vol 34 (1-4) ◽  
pp. 367-378 ◽  
Author(s):  
Gerhard Frank ◽  
Thomas Härtl ◽  
Jochen Tschiersch
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image

scholarly journals Classification of polymers insulators hydrophobicity basead on digital image processing

2012 ◽  
Vol 15 (3) ◽  
pp. 365-371 ◽  
Author(s):  
Daniel Thomazini ◽  
Maria Virginia Gelfuso ◽  
Ruy Alberto Corrêa Altafim
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image

Digital Image Processing for On-line Classification of Partial Discharge Patterns in Electrical Equipment

2007 ◽  
Vol 5 (5) ◽  
pp. 287-293
Author(s):  
V.R. Garcia-Colon ◽  
R. Gonzalez Melchor ◽  
M.E. Hernandez Valois
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Partial Discharge ◽  
Electrical Equipment ◽  
On Line ◽  
Discharge Patterns ◽  
Line Classification

Digital Image Processing for Classification of Coffee Cherries

2010 ◽  
Author(s):  
Zulma Sandoval ◽  
Flavio Prieto ◽  
Julian Betancur
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image
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