scholarly journals Geometrical structure of perceptual color space is affine

2013 ◽  
Vol 13 (9) ◽  
pp. 295-295
Author(s):  
R. Ennis ◽  
Q. Zaidi
Keyword(s):  
Geometrical Structure ◽  
Color Space

scholarly journals Geometrical structure of perceptual color space: mental representations and adaptation invariance

2018 ◽  
Author(s):  
Robert J Ennis ◽  
Qasim Zaidi
Keyword(s):  
Mental Representation ◽  
Neural Coding ◽  
Geometrical Structure ◽  
Color Space ◽  
Physical Space ◽  
Affine Geometry ◽  
Representation Space ◽  
Perceptual Space ◽  
Color Spaces ◽  
Opponent Color

AbstractA central issue in neuroscience is to understand how the brain builds structured representations of percepts that facilitate useful inferences about the world. Similarity between percepts is used to accomplish many everyday tasks, e.g. object identification, so is widely used to construct geometrical spaces that represent stimulus qualities, but the intrinsic validity of the geometry is not tested critically. We introduce an experimental approach to equating relative similarities by setting perceived midpoints between pairs of stimuli. Midpoint settings are used with Varignon’s Theorem to test the intrinsic geometry of a representation space, and its mapping to a physical space of stimuli. For perceptual color space, we demonstrate that geometrical structure depends on the mental representation used in judging similarity: an affine geometry is valid only when observers use an opponent-color mental representation. An affine geometry implies that similarity can be judged within straight lines and across parallel lines, and its neural coding could involve ratios of responses. We show that this perceptual space is invariant to changes in illumination color, providing a formal justification to generalize to all of color space, color constancy results measured for color categories. Our midpoint measurements deviate significantly from midpoints in the “uniform” color spaces CIELAB and CIELUV, used extensively in industry and research, so these spaces do not provide adequate metric representation of perceived colors. Our paradigm can thus test for intrinsic geometrical assumptions underlying the representation space for many perceptual modalities, and for the extrinsic perceptual geometry of the space of physical stimuli.SignificanceMathematical spaces based on similarity judgments are widely used to represent stimulus qualities in perception, cognition and neuroscience. We introduce a perceptual approach to equate relative similarities, and use them to test the geometry of a perceptual space and its mapping to a physical space of stimuli. For color perception, our results show that perceptual geometry depends on the mental representation used in judging similarity, and it has an affine structure when observers use an opponent-color representation. An affine geometry implies that neural coding of similarity could involve simple ratios of responses. Our measurements also reveal that the uniform color spaces CIELAB and CIELUV, used extensively in industrial applications, do not provide adequate representation of similarity between moderately spaced colors.

Indo study of the geometrical structure of NCNCO

1978 ◽  
Vol 75 ◽  
pp. 703-705 ◽  
Author(s):  
Swadesh Ranjan Samanta ◽  
Ali Uddin Shaikh ◽  
Mahamed Asgar Ali
Keyword(s):  
Geometrical Structure

IDEAL COLOR SPACE COMPONENT FOR RECONSTRUCTION OF CONTAMINATION PLUMES

2013 ◽  
Vol 20 (3) ◽  
pp. 125-159 ◽  
Author(s):  
Sina Kashuk ◽  
Sophia R. Mercurio ◽  
Magued Iskander
Keyword(s):  
Color Space

Color Space Transformation using Neural Networks

2019 ◽  
Vol 2019 (1) ◽  
pp. 153-158
Author(s):  
Lindsay MacDonald
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Color Space ◽  
Reflectance Spectra ◽  
Network Architectures ◽  
Color Spaces ◽  
Natural Materials ◽  
Space Transformation ◽  
Color Space Transformation

We investigated how well a multilayer neural network could implement the mapping between two trichromatic color spaces, specifically from camera R,G,B to tristimulus X,Y,Z. For training the network, a set of 800,000 synthetic reflectance spectra was generated. For testing the network, a set of 8,714 real reflectance spectra was collated from instrumental measurements on textiles, paints and natural materials. Various network architectures were tested, with both linear and sigmoidal activations. Results show that over 85% of all test samples had color errors of less than 1.0 ΔE2000 units, much more accurate than could be achieved by regression.

A Correspondence-Free Color Chart Design for Color Calibration

2020 ◽  
Vol 2020 (1) ◽  
pp. 100-104
Author(s):  
Hakki Can Karaimer ◽  
Rang Nguyen
Keyword(s):  
Color Space ◽  
Fixed Number ◽  
New Approach ◽  
Color Chart ◽  
Color Calibration ◽  
Space Transformation ◽  
Color Space Transformation ◽  
Chart Design ◽  
Calibration Approach

Colorimetric calibration computes the necessary color space transformation to map a camera's device-specific color space to a device-independent perceptual color space. Color calibration is most commonly performed by imaging a color rendition chart with a fixed number of color patches with known colorimetric values (e. g., CIE XYZ values). The color space transformation is estimated based on the correspondences between the camera's image and the chart's colors. We present a new approach to colorimetric calibration that does not require explicit color correspondences. Our approach computes a color space transformation by aligning the color distributions of the captured image to the known distribution of a calibration chart containing thousands of colors. We show that a histogram-based colorimetric calibration approach provides results that are onpar with the traditional patch-based method without the need to establish correspondences.

Pencarian File Gambar Berdasarkan Dominasi Warna

2011 ◽  
Vol 2 (1) ◽  
Author(s):  
Vina Chovan Epifania ◽  
Eko Sediyono
Keyword(s):  
Digital Image ◽  
Retrieval System ◽  
Color Image ◽  
Color Space ◽  
Image Data ◽  
Image Search ◽  
Test Results ◽  
Application Form ◽  
Space Model ◽  
Image File

Abstract. Image File Searching Based on Color Domination. One characteristic of an image that can be used in image searching process is the composition of the colors. Color is a trait that is easily seen by man in the picture. The use of color as a searching parameter can provide a solution in an easier searching for images stored in computer memory. Color images have RGB values that can be computed and converted into HSL color space model. Use of HSL images model is very easy because it can be calculated using a percent, so that in each pixel of the image can be grouped and named, this can give a dominant values of the colors contained in one image. By obtaining these values, the image search can be done quickly just by using these values to a retrieval system image file. This article discusses the use of the HSL color space model to facilitate the searching for a digital image in the digital image data warehouse. From the test results of the application form, a searching is faster by using the colors specified by the user. Obstacles encountered were still searching with a choice of 15 basic colors available, with a limit of 33% dominance of the color image search was not found. This is due to the dominant color in each image has the most dominant value below 33%.   Keywords: RGB, HSL, image searching Abstrak. Salah satu ciri gambar yang dapat dipergunakan dalam proses pencarian gambar adalah komposisi warna. Warna adalah ciri yang mudah dilihat oleh manusia dalam citra gambar. Penggunaan warna sebagai parameter pencarian dapat memberikan solusi dalam memudahkan pencarian gambar yang tersimpan dalam memori komputer. Warna gambar memiliki nilai RGB yang dapat dihitung dan dikonversi ke dalam model HSL color space. Penggunaan model gambar HSL sangat mudah karena dapat dihitung dengan menggunakan persen, sehingga dalam setiap piksel gambar dapat dikelompokan dan diberi nama, hal ini dapat memberikan suatu nilai dominan dari warna yang terdapat dalam satu gambar. Dengan diperolehnya nilai tersebut, pencarian gambar dapat dilakukan dengan cepat hanya dengan menggunakan nilai tersebut pada sistem pencarian file gambar. Artikel ini membahas tentang penggunaan model HSL color space untuk mempermudah pencarian suatu gambar digital didalam gudang data gambar digital. Dari hasil uji aplikasi yang sudah dibuat, diperoleh pencarian yang lebih cepat dengan menggunakan pilihan warna yang ditentukan sendiri oleh pengguna. Kendala yang masih dijumpai adalah pencarian dengan pilihan 15 warna dasar yang tersedia, dengan batas dominasi warna 33% tidak ditemukan gambar yang dicari. Hal ini disebabkan warna dominan disetiap gambar kebanyakan memiliki nilai dominan di bawah 33%. Kata Kunci: RGB, HSL, pencarian gambar

HSV color space based pupil position locating method

2014 ◽  
Author(s):  
Peng Cao ◽  
Qijie Zhao ◽  
Dawei Tu ◽  
Hui Shao
Keyword(s):  
Color Space ◽  
Hsv Color Space

FOREGROUND IMAGE EXTRCTION IN THE HSV COLOR SPACE

2010 ◽  
Vol 7 (7) ◽  
pp. 1-4
Author(s):  
Jyh-Yeong Chang ◽  
Jia-Jye Shyu ◽  
Yi-Cheng Luo
Keyword(s):  
Color Space ◽  
Hsv Color Space
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