Performance of Color Cascading Framework on Different Color-Space for Malaria Identification

2018 ◽  
Author(s):  
Ari Kusumaningsih ◽  
Yonathan Ferry Hendrawan ◽  
Cucun Very Angkoso ◽  
Rima Tri Wahyuningrum
Keyword(s):  
Color Space ◽  
Different Color

scholarly journals What we talk about when we talk about color

2020 ◽  
Author(s):  
Colin R. Twomey ◽  
Gareth Roberts ◽  
David Brainard ◽  
Joshua B. Plotkin
Keyword(s):  
Visible Light ◽  
Color Space ◽  
Color Perception ◽  
Geographic Location ◽  
Cross Cultural ◽  
Cultural Variation ◽  
Inference Algorithm ◽  
Color Categories ◽  
New Directions ◽  
Different Color

Names for colors vary widely across languages, but color categories are remarkably consistent [1–5]. Shared mechanisms of color perception help explain consistent partitions of visible light into discrete color vocabularies [6–10]. But the mappings from colors to words are not identical across languages, which may reflect communicative needs – how often speakers must refer to objects of different color [11]. Here we quantify the communicative needs of colors in 130 different languages, using a novel inference algorithm. Some regions of color space exhibit 30-fold greater demand for communication than other regions. The regions of greatest demand correlate with the colors of salient objects, including ripe fruits in primate diets. Using the mathematics of compression we predict and empirically test how languages map colors to words, accounting for communicative needs. We also document extensive cultural variation in communicative demands on different regions of color space, which is partly explained by differences in geographic location and local biogeography. This account reconciles opposing theories for universal patterns in color vocabularies, while opening new directions to study cross-cultural variation in the need to communicate different colors.

Comparative Experiment of Color Reproduction Methods

2014 ◽  
Vol 1051 ◽  
pp. 967-970
Author(s):  
Qi Jia ◽  
Xu Liang Lv ◽  
Wei Dong Xu ◽  
Jiang Hua Hu ◽  
Xian Hui Rong
Keyword(s):  
Polynomial Regression ◽  
Rapid Development ◽  
Color Space ◽  
Digital Camera ◽  
Color Difference ◽  
High Tech ◽  
Comparative Experiment ◽  
Color Reproduction ◽  
Different Color ◽  
Time Image

Digital camera which has the advantage of real-time image transferring and easily processing is more and more widely used in the packaging and printing industry with the rapid development of high-tech electronics industry. However, the color in digital camera is not accurate which affect the application. To minimize the color difference between the color in the digital camera and the real color, the color reproduction methods is developing. The field comparative experiment is carried out to compare the performance of color reproduction methods, such as polynomial regression algorithm in different color space, and color checker passport. The results show that fourth order polynomial regression color reproduction in XYZ color space has the best performance.

Estimation of Fractal Dimension in Different Color Model

2018 ◽  
Vol 8 (1) ◽  
pp. 75-93
Author(s):  
Sumitra Kisan ◽  
Sarojananda Mishra ◽  
Ajay Chawda ◽  
Sanjay Nayak
Keyword(s):  
Fractal Dimension ◽  
Color Space ◽  
Vital Role ◽  
Color Images ◽  
Color Spaces ◽  
Fractal Surfaces ◽  
Test Operation ◽  
Novel Method ◽  
Rgb Color Space ◽  
Different Color

This article describes how the term fractal dimension (FD) plays a vital role in fractal geometry. It is a degree that distinguishes the complexity and the irregularity of fractals, denoting the amount of space filled up. There are many procedures to evaluate the dimension for fractal surfaces, like box count, differential box count, and the improved differential box count method. These methods are basically used for grey scale images. The authors' objective in this article is to estimate the fractal dimension of color images using different color models. The authors have proposed a novel method for the estimation in CMY and HSV color spaces. In order to achieve the result, they performed test operation by taking number of color images in RGB color space. The authors have presented their experimental results and discussed the issues that characterize the approach. At the end, the authors have concluded the article with the analysis of calculated FDs for images with different color space.

scholarly journals Color Image Segmentation Based on Different Color Space Models Using Automatic GrabCut

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Dina Khattab ◽  
Hala Mousher Ebied ◽  
Ashraf Saad Hussein ◽  
Mohamed Fahmy Tolba
Keyword(s):  
Image Segmentation ◽  
Comparative Study ◽  
Color Image ◽  
Color Space ◽  
User Interaction ◽  
Color Image Segmentation ◽  
Space Representation ◽  
Color Spaces ◽  
Different Color ◽  
The Comparative Study

This paper presents a comparative study using different color spaces to evaluate the performance of color image segmentation using the automatic GrabCut technique. GrabCut is considered as one of the semiautomatic image segmentation techniques, since it requires user interaction for the initialization of the segmentation process. The automation of the GrabCut technique is proposed as a modification of the original semiautomatic one in order to eliminate the user interaction. The automatic GrabCut utilizes the unsupervised Orchard and Bouman clustering technique for the initialization phase. Comparisons with the original GrabCut show the efficiency of the proposed automatic technique in terms of segmentation, quality, and accuracy. As no explicit color space is recommended for every segmentation problem, automatic GrabCut is applied withRGB,HSV,CMY,XYZ, andYUVcolor spaces. The comparative study and experimental results using different color images show thatRGBcolor space is the best color space representation for the set of the images used.

Size Induction Transcends the Cardinal Directions of Color Space

Perception ◽  
1993 ◽  
Vol 22 (7) ◽  
pp. 841-845
Author(s):  
Jeff Rabin ◽  
Anthony J Adams
Keyword(s):  
Visual Perception ◽  
Test Object ◽  
Color Space ◽  
Colour Space ◽  
Early Stages ◽  
Cardinal Directions ◽  
Different Color ◽  
Level Of Processing

Certain psychophysical phenomena occur separately for color and for luminance stimulation. Separate psychophysical effects have also been elicited along different directions in equiluminant colour space. Whereas in most studies in which separate luminance and color effects have been reported the authors have used successive-adaptation approaches, less is known about the separateness of color and luminance processing under simultaneous conditions. A study is reported in which simultaneous size induction was examined for several different color directions thought to be ‘cardinal’ for early stages of processing. The perceived size of a test object was influenced by the size of the surrounding objects regardless of the color direction of the test and induction objects. The results indicate that simultaneous size induction occurs at a level of processing at which information conveyed by color and by luminance mechanisms is compared and contrasted to influence visual perception.

scholarly journals Comparison of the color selectivity of macaque V4 neurons in different color spaces

2016 ◽  
Vol 116 (5) ◽  
pp. 2163-2172 ◽  
Author(s):  
Takahisa M. Sanada ◽  
Tomoyuki Namima ◽  
Hidehiko Komatsu
Keyword(s):  
Visual Processing ◽  
Color Space ◽  
Limited Range ◽  
Color Information ◽  
Color Representation ◽  
Visual Areas ◽  
Color Selectivity ◽  
Different Color ◽  
V4 Neurons ◽  
Higher Visual Areas

Chromatic selectivity has been studied extensively in various visual areas at different stages of visual processing in the macaque brain. In these studies, color stimuli defined in the Derrington-Krauskopf-Lennie (DKL) color space with a limited range of cone contrast were typically used in early stages, whereas those defined in the Commission Internationale de l'Eclairage (CIE) color space, based on human psychophysical measurements across the gamut of the display, were often used in higher visual areas. To understand how the color information is processed along the visual pathway, it is necessary to compare color selectivity obtained in different areas on a common color space. In the present study, we tested whether the neural color selectivity obtained in DKL space can be predicted from responses obtained in CIE space and whether stimuli with limited cone contrast are sufficient to characterize neural color selectivity. We found that for most V4 neurons, there was a strong correlation between responses measured using the two chromatic coordinate systems, and the color selectivities obtained with the two stimulus sets were comparable. However, for some neurons preferring high- or low-saturation colors, stimuli defined in DKL color space did not adequately capture the neural color selectivity. This is mainly due to the use of stimuli within a limited range of cone contrast. We conclude that regardless of the choice of color space, the sampling of colors across the entire gamut is important to characterize neural color selectivity fully or to compare color selectivities in different areas so as to understand color representation in the visual system.

Study on Reproduction of Color Information of Digital Image Based on Different Color Gamut

2012 ◽  
Vol 430-432 ◽  
pp. 838-841
Author(s):  
Wen Ge Chen
Keyword(s):  
Image Processing ◽  
Digital Image ◽  
Color Space ◽  
Mapping Method ◽  
Color Information ◽  
Color Gamut ◽  
Gamut Mapping ◽  
Processing Software ◽  
Image Processing Software ◽  
Different Color

This paper is based on digital image color information reproduction error in a different color gamut,Through the different color gamut mapping method, image processing software Photoshop is used to make experiment and to obtain the corresponding image effect. Using digital presses to print out and use Spectrodensitometer measure the corresponding data.Using Excel software for data processing and analysis, digital image color information of loss situation is obtained in RGB and CMYK color space, It can provide certain basis for control of the color loss.

scholarly journals Improving Color Space Conversion for Camera-Captured Images via Wide-Gamut Metadata

2020 ◽  
Vol 2020 (28) ◽  
pp. 193-198
Author(s):  
Hoang Le ◽  
Mahmoud Afifi ◽  
Michael S. Brown
Keyword(s):  
Color Space ◽  
Mapping Function ◽  
Mapping Method ◽  
Color Spaces ◽  
Color Gamut ◽  
Color Mapping ◽  
Color Space Conversion ◽  
Different Color ◽  
Image Format ◽  
Image State

Color space conversion is the process of converting color values in an image from one color space to another. Color space conversion is challenging because different color spaces have different sized gamuts. For example, when converting an image encoded in a medium-sized color gamut (e.g., AdobeRGB or Display-P3) to a small color gamut (e.g., sRGB), color values may need to be compressed in a many-to-one manner (i.e., multiple colors in the source gamut will map to a single color in the target gamut). If we try to convert this sRGB-encoded image back to a wider gamut color encoding, it can be challenging to recover the original colors due to the color fidelity loss. We propose a method to address this problem by embedding wide-gamut metadata inside saved images captured by a camera. Our key insight is that in the camera hardware, a captured image is converted to an intermediate wide-gamut color space (i.e., ProPhoto) as part of the processing pipeline. This wide-gamut image representation is then saved to a display color space and saved in an image format such as JPEG or HEIC. Our method proposes to include a small sub-sampling of the color values from the ProPhoto image state in the camera to the final saved JPEG/HEIC image. We demonstrate that having this additional wide-gamut metadata available during color space conversion greatly assists in constructing a color mapping function to convert between color spaces. Our experiments show our metadata-assisted color mapping method provides a notable improvement (up to 60% in terms of E) over conventional color space methods using perceptual rendering intent. In addition, we show how to extend our approach to perform adaptive color space conversion based spatially over the image for additional improvements.

scholarly journals Impacts of Color Space Transformations on Dysplastic Nuclei Segmentation Using CNN

2020 ◽  
Author(s):  
Dalí Dos Santos ◽  
Adriano Silva ◽  
Paulo De Faria ◽  
Bruno Travençolo ◽  
Marcelo Do Nascimento
Keyword(s):  
Color Space ◽  
Precancerous Lesion ◽  
Epithelial Dysplasia ◽  
Color Spaces ◽  
Oral Epithelial Dysplasia ◽  
Nuclei Segmentation ◽  
Space Transformation ◽  
Different Color ◽  
Oral Epithelial ◽  
The Impact

Oral epithelial dysplasia is a common precancerous lesion type that can be graded as mild, moderate and severe. Although not all oral epithelial dysplasia become cancer over time, this premalignant condition has a significant rate of progressing to cancer and the early treatment has been shown to be considerably more successful. The diagnosis and distinctions between mild, moderate, and severe grades are made by pathologists through a complex and time-consuming process where some cytological features, including nuclear shape, are analysed. The use of computer-aided diagnosis can be applied as a tool to aid and enhance the pathologist decisions. Recently, deep learning based methods are earning more and more attention and have been successfully applied to nuclei segmentation problems in several scenarios. In this paper, we evaluated the impact of different color spaces transformations for automated nuclei segmentation on histological images of oral dysplastic tissues using fully convolutional neural networks (CNN). The CNN were trained using different color spaces from a dataset of tongue images from mice diagnosed with oral epithelial dysplasia. The CIE L*a*b* color space transformation achieved the best averaged accuracy over all analyzed color space configurations (88.2%). The results show that the chrominance information, or the color values, does not play the most significant role for nuclei segmentation purpose on a mice tongue histopathological images dataset.

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