Symbolic Pointillism: Computer Art Motivated by Human Brain Structures

Leonardo ◽  
2005 ◽  
Vol 38 (4) ◽  
pp. 337-340 ◽  
Author(s):  
Norbert Krüger ◽  
Florentin Wörgötter
Keyword(s):  
Visual System ◽  
Human Brain ◽  
Human Visual System ◽  
Vision System ◽  
Visual Representations ◽  
Brain Structures ◽  
Human Vision ◽  
Artificial Vision ◽  
Computer Art ◽  
Functional Aspects

The authors introduce a new kind of computer art motivated by cortical structures in the human visual system. This type of computer art is related to the sub-group of the impressionist art movement called pointillism. However, while pointillism visualizes and makes use of processes that have been associated with the human eye, Symbolic Pointillism also makes cortical processes explicit. The visual representations underlying this art have been developed during a project that aims at the transfer of functional aspects of human vision to artificial systems. The authors have applied their findings in such an artificial vision system and in a sound/vision installation.

The Study of Spatial Frequency Channels for Human Visual System

2019 ◽  
Vol 33 (06) ◽  
pp. 1955007
Author(s):  
Xiangyang Xu ◽  
Qiao Chen ◽  
Ruixin Xu
Keyword(s):  
Receptive Field ◽  
Spatial Frequency ◽  
Visual System ◽  
Human Visual System ◽  
Frequency Tuning ◽  
Tuning Curve ◽  
Vision System ◽  
Human Vision ◽  
Psychophysical Experiment ◽  
Human Vision System

Similar to auditory perception of sound system, color perception of the human visual system also presents a multi-frequency channel property. In order to study the multi-frequency channel mechanism of how the human visual system processes color information, the paper proposed a psychophysical experiment to measure the contrast sensitivities based on 17 color samples of 16 spatial frequencies on CIELAB opponent color space. Correlation analysis was carried out on the psychophysical experiment data, and the results show obvious linear correlations of observations for different spatial frequencies of different observers, which indicates that a linear model can be used to model how human visual system processes spatial frequency information. The results of solving the model based on the experiment data of color samples show that 9 spatial frequency tuning curves can exist in human visual system with each lightness, R–G and Y–B color channel and each channel can be represented by 3 tuning curves, which reflect the “center-around” form of the human visual receptive field. It is concluded that there are 9 spatial frequency channels in human vision system. The low frequency tuning curve of a narrow-frequency bandwidth shows the characteristics of lower level receptive field for human vision system, the medium frequency tuning curve shows a low pass property of the change of medium frequent colors and the high frequency tuning curve of a width-frequency bandwidth, which has a feedback effect on the low and medium frequency channels and shows the characteristics of higher level receptive field for human vision system, which represents the discrimination of details.

Organix

2010 ◽  
Vol 1 (1) ◽  
pp. 40-53
Author(s):  
Robert J. Hendley ◽  
Barry Wilkins ◽  
Russell Beale
Keyword(s):  
Visual System ◽  
Cognitive Processing ◽  
Growth Model ◽  
Human Visual System ◽  
Visual Representations ◽  
Text Documents ◽  
Organic Growth

This article presents a mechanism for generating visually appealing but also effective representations for document visualisation. The mechanism is based on an organic growth model which is driven by features of the object to be visualised. In the examples used, the authors focus on the visualisation of text documents, but the methods are readily transferable to other domains. They are also scaleable to documents of any size.The objective of this research is to build visual representations that enable the human visual system to efficiently and effectively recognise documents without the need for higher level cognitive processing. In particular, the authors want the user to be able to recognise similarities within sets of documents and to be able to easily discriminate between dissimilar objects.

scholarly journals Tinjauan Literatur Sistematik tentang Structural Similarity Index Measure untuk Deteksi Anomali Gambar

2021 ◽  
Vol 7 (2) ◽  
pp. 75
Author(s):  
Halim Bayuaji Sumarna ◽  
Ema Utami ◽  
Anggit Dwi Hartanto
Keyword(s):  
Image Quality ◽  
Image Enhancement ◽  
Human Visual System ◽  
Vision System ◽  
Similarity Index ◽  
Structural Similarity ◽  
Human Vision ◽  
Human Vision System ◽  
Structural Similarity Index ◽  
Index Measure

Image enhancement merupakan prosedur yang digunakan untuk memproses gambar sehingga dapat memperbaiki atau meningkatkan kualitas gambar agar selanjutnya dapat dianalis untuk tujuan tertentu. Ada banyak algoritma image enhancement yang dapat diterapkan pada suatu gambar, salah satunya dapat menggunakan algoritma structural similarity index measure (SSIM), algoritma ini berfungsi sebagai alat ukur dalam menilai kualitas gambar, bekerja dengan membandingkan fitur structural dari gambar, dan kualitas gambar dijelaskan oleh kesamaan structural. Selain untuk menilai kualitas suatu gambar, SSIM dapat menjadi metode dalam menganalisis perbedaan gambar, sehingga diketahui anomali dari perbandingan dua gambar berdasarkan data structural dari sebuah gambar. Tinjauan literature sistematis ini digunakan untuk menganalisis dan fokus pada algoritma SSIM dalam mengetahui anomaly 2 gambar yang terlihat mirip secara human visual system. Hasil sistematis review menunjukkan bahwa penggunaan algoritma SSIM dalam menilai kualitas gambar berkorelasi kuat dengan HVS (Human Vision System) dan dalam deteksi anomaly gambar menghasilkan akurasi yang berbeda, karena terpengaruh intensitas cahaya dan posisi kamera dalam mengambil gambar sebagai dataset.Kata Kunci— SSIM, anomaly, gambar, deteksiImage enhancement is a procedure used to process images so that they can correct or improve image quality so that they can then be analyzed for specific purposes. Many image enhancement algorithms can be applied to an image. one of the usable methods is the structural similarity index measure (SSIM) algorithm, this algorithm serves as a measuring tool in assessing image quality. It works by comparing the structural features of images, and the image quality is explained by structural similarity. In addition to assessing the quality of an image, SSIM can be a method of analyzing image differences. So, the anomalies are known from the comparison of two images based on the structural data from an image. This systematic literature review is used to analyze and focus on the SSIM algorithm in knowing anomaly 2 images that look similar to the human visual system. Systematic review results show that the use of the SSIM algorithm in assessing image quality is strongly correlated with HVS (Human Vision System). In anomaly detection of images produces different accuracy because it is affected by light intensity and camera position in taking pictures as a dataset.Keywords— SSIM, anomaly, gambar, deteksi

Overview of industrial machine vision

1984 ◽  
Vol 42 ◽  
pp. 550-553
Author(s):  
Jon R. Mandeville
Keyword(s):  
Machine Vision ◽  
Cognitive Processing ◽  
Vision System ◽  
Human Vision ◽  
Artificial Vision ◽  
Visual Environment ◽  
Computational System ◽  
Visual Sensing ◽  
Significant Research ◽  
Industrial Machine

One hardly needs to emphasize the importance of visual sensing and interpretation in our everyday lives and the severe limitations and handicaps imposed on the blind. The importance of human vision has motivated an intense interest in and significant research on artificial vision systems over the last 20 years. The relatively new, fast growing discipline of “machine (or computer) vision” is an outgrowth of this research.Machine vision is computation on images to produce useful, meaningful descriptions of a visual environment. A machine vision system may be used either as a symbiotic enhancement to human vision or as the perceptual component of an autonomous, goal-driven computational system capable of cognitive processing.

Technical Vision Model of the Visual Systems for Industry Application

2021 ◽  
pp. 288-310
Author(s):  
Oleg Sytnik ◽  
Vladimir Kartashov
Keyword(s):  
Image Processing ◽  
Pattern Recognition ◽  
Visual System ◽  
Mathematical Models ◽  
Human Visual System ◽  
Vision System ◽  
Vision Systems ◽  
Industrial Systems ◽  
Visual Systems ◽  
Technical Vision

The problems of highlighting the main informational aspects of images and creating their adequate models are discussed in the chapter. Vision systems can receive information about an object in different frequency ranges and in a form that is not accessible to the human visual system. Vision systems distort the information contained in the image. Therefore, to create effective image processing and transmission systems, it is necessary to formulate mathematical models of signals and interference. The chapter discusses the features of perception by the human visual system and the issues of harmonizing the technical characteristics of industrial systems for receiving and transmitting images. Methods and algorithms of pattern recognition are discussed. The problem of conjugation of the characteristics of the technical vision system with the consumer of information is considered.

scholarly journals Exploiting ambiguity: The diffraction artefact and the architectural surface

2019 ◽  
Vol 17 (1) ◽  
pp. 103-115
Author(s):  
Linda Matthews ◽  
Gavin Perin
Keyword(s):  
Visual System ◽  
Urban Space ◽  
Digital Imaging ◽  
Human Visual System ◽  
Human Vision ◽  
System Model ◽  
The Political ◽  
Transmission Pipeline ◽  
Image Production ◽  
Vantage Points

In the contemporary ‘envisioned’ environment, Internet webcams, low- and high-altitude unmanned aerial vehicles and satellites are the new vantage points from which to construct the image of the city. Armed with hi-resolution digital optical technologies, these vantage points effectively constitute a ubiquitous visioning apparatus serving either the politics of promotion or surveillance. Given the political dimensions of this apparatus, it is important to note that this digital imaging of public urban space refers to the human visual system model. In order to mimic human vision, a set of algorithm patterns are used to direct numerous ‘soft’ and ‘hard’ technologies. Mimicry thus has a cost because this insistence on the human visual system model necessitates multiple transformative moments in the production and transmission pipeline. If each transformative moment opens a potential vulnerability within the visioning apparatus, then every glitch testifies to the artificiality of the image. Moreover, every glitch potentially interrupts the political narratives be communicated in contemporary image production and transmission. Paradoxically, the current use of scripting to create glitch-like images has reimagined glitches as a discrete aesthetic category. This article counters this aestheticisation by asserting glitching as a disruption in communication. The argument will rely on scaled tests produced by one of the authors who show how duplicating the digital algorithmic patterns used within the digital imaging pipeline on any exterior building surface glitches the visual data captured within that image. Referencing image-based techniques drawn from the Baroque and contemporary modes of camouflage, it will be argued that the visual aberrations created by these algorithm-based patterned facades can modify strategically the ‘emission signature’ of selected parts of the urban fabric. In this way, the glitch becomes a way to intercede in the digital portrayal of city.

Relationships between Channels for Colour and Spatial Frequency in Human Vision

Perception ◽  
1973 ◽  
Vol 2 (1) ◽  
pp. 31-40 ◽  
Author(s):  
V Virsu ◽  
S Haapasalo
Keyword(s):  
Spatial Frequency ◽  
Visual System ◽  
Human Visual System ◽  
Human Vision ◽  
Visual Objects ◽  
The Third ◽  
Simultaneous Integration ◽  
Two Systems ◽  
Channel Systems

Five forms of relationships and four types of channels are possible between two systems of sensory channels. The relationships between channels for colour and spatial frequency were studied in three adaptation experiments. In the first, a new colour-specific spatial aftereffect was found, which indicates the existence of channels that are specific both to colour and to spatial frequency. The second showed that the spatial-frequency aftereffect of Blakemore and Sutton is not colour specific, which indicates that there are channels for spatial frequency that are not colour specific. The third demonstrated that coloured afterimages are not spatial-frequency specific immediately after adaptation, although they become so later. This indicates that there are channels for colour that are not spatial-frequency specific. The existence of these three types of channels implies that the channel systems for colour and spatial frequency overlap partially and mutually in the human visual system. This kind of organisation of channel systems, if it exists, may form the psychophysical structure that is required for the capacity of simultaneous integration and differentiation in the perception of colour and size of visual objects.

Are Curves Detected by ‘Curvature Detectors’?

Perception ◽  
1978 ◽  
Vol 7 (1) ◽  
pp. 51-64 ◽  
Author(s):  
Brian N Timney ◽  
Colin Macdonald
Keyword(s):  
Visual System ◽  
Human Visual System ◽  
Human Vision ◽  
Orientation Tuning ◽  
Threshold Elevation ◽  
Maximum Value ◽  
Adaptation Experiment ◽  
The Relationship

Five experiments which attempted to evaluate the relationship between orientation and curvature selectivity in human vision are described. In the first two experiments, threshold elevation for curved gratings was measured after exposure to similar gratings, with the use of either an adaptation (experiment 1) or a masking (experiment 2) paradigm. In both experiments threshold elevation occurred which was selective for both the degree and the direction of curvature of the adapting pattern. Experiment 3 compared the effects of adapting to tilted rectilinear or vertical curved gratings upon threshold for a vertical rectilinear grating. Threshold elevation declined systematically as the adapting gratings were either tilted or made more curved. Experiment 4 measured curvature selectivity as a function of the orientation of a curved adapting grating. Threshold elevation declined as the adapting grating was tilted more, but curvature selectivity remained. Experiment 5 measured the orientation tuning for curved gratings directly. Threshold elevation declined to 50% of its maximum value at an adapting orientation of about 28°. This was constant for all values of curvature used. The results are discussed with reference to the question of whether the human visual system contains ‘curvature detectors’ or linear-contour detectors which respond to the tangents of curves.

Monochromatic Leds For Vision Improvement in Foggy Roads

2021 ◽  
pp. 108-113
Author(s):  
Shovakar Bhattacharjee ◽  
Arnab De ◽  
Arijit Saha ◽  
Saswati Mazumdar
Keyword(s):  
Adverse Effect ◽  
Visual System ◽  
Vision System ◽  
Monochromatic Light ◽  
Green Light ◽  
Monochromatic Radiation ◽  
Artificial Vision ◽  
Long Distance ◽  
Amber Light ◽  
Traffic Speed

In India, foggy weather creates poor visibility, and this leads to several accidents and slows down normal traffic speed, which may lead to adverse effect on the economy of the country. The probable solution is the use of monochromatic light with other artificial vision system to increase the visibility for the drivers in these foggy areas. There are various kinds of monochromatic lights available in the market. In this study, it has been tried to find out the best working monochromatic LEDs for this particular application. In this study, two types of monochromatic radiation were compared (amber light with 600 nm and green light with 545 nm) with and without the camera-display setup (artificial visual system) for finding out best working system in the foggy area for increasing the visibility. The experiment shows that amber light monochromatic radiation with 600 nm works better for identification of objects. The amber light can be used in front of a car to illuminate the front environment in the foggy weather and increase the visibility. It has been observed that green light monochromatic radiation with 545 nm works better for identification of the source from a very long distance. It has been proposed to install both of these lights with amber and green monochromatic radiation in vehicles to reduce accidents in foggy weather.

Organix

2012 ◽  
pp. 34-46
Author(s):  
Robert J. Hendley ◽  
Barry Wilkins ◽  
Russell Beale
Keyword(s):  
Visual System ◽  
Cognitive Processing ◽  
Growth Model ◽  
Human Visual System ◽  
Visual Representations ◽  
Text Documents ◽  
Organic Growth

This paper presents a mechanism for generating visually appealing but also effective representations for document visualisation. The mechanism is based on an organic growth model which is driven by features of the object to be visualised. In the examples used, the authors focus on the visualisation of text documents, but the methods are readily transferable to other domains. They are also scaleable to documents of any size. The objective of this research is to build visual representations that enable the human visual system to efficiently and effectively recognise documents without the need for higher level cognitive processing. In particular, the authors want the user to be able to recognise similarities within sets of documents and to be able to easily discriminate between dissimilar objects.

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