A skillet-based recoloring algorithm for dichromats

Ribeiro, Madalena; Gomes, Abel

doi:10.1109/healthcom.2013.6720766

Cited by 12 publications

(4 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The authors employed optimization based recoloring methods using two color rotation steps in CIELAB color space. A compensation algorithm which eliminates the confusion between red and green colors was created in 2013 by Abel J. P. Gomes and Madalena G. Ribeiro (14). The authors remap the red region excluding the green color using the maximum saturation to promise that the couple of different hues are mapped onto two diverse hues.…”

Section: Color Compensation Algorithmsmentioning

confidence: 99%

“…Let f = [fr, fg, fb] represent the original image containing three color groups: r, g and b. αp, αd and αt represent the degree of fuzziness of red, green and blue-yellow blindness respectively. Equations [12], [13] and [14] show the correction for red, green and blue-yellow blindness respectively by adjustment of the non-confusing components present in the confusion color.…”

Section: Figure V Simulated Images For Varying Degrees Of Blue-yellow...mentioning

confidence: 99%

See 1 more Smart Citation

A Fuzzy Based Method to Simulate and Color Correct Images for Varying Degrees of Color Blindness

Meenakshi¹,

Singla²

2022

ECS Trans.

View full text Add to dashboard Cite

Eyesight is a key sense that human beings possess. Reports shows that color blindness, one form of color vision deficiency(CVD), touches about 8% of the males and 0.5% females (1). Patients of color blindness are unable to differentiate certain colors called confusion colors. Inability to differentiate red results in red blindness, green in green blindness, and blue/yellow in blue-yellow blindness. Routine activities of daily life become a challenge for the colorblind due to this inability. Digital solutions in the area of computer vision can be used to make lives easier for the colorblind (2). The authors propose a fuzzy based method to simulate and compensate confusion colors in images for varying degrees of color blindness. Experiments were conducted on images for simulation and color compensation. Observations of the color compensation was measured with normal vision and colorblind patients. It resulted in 91% accuracy for red green color blindness. The efficiency of simulation was measured by evaluation with state-of-the-art online tools and literature. The results show 95.8% accuracy. The results obtained affirms the efficiency of the proposed fuzzy method.

show abstract

Section: Color Compensation Algorithmsmentioning

confidence: 99%

Section: Figure V Simulated Images For Varying Degrees Of Blue-yellow...mentioning

confidence: 99%

A Fuzzy Based Method to Simulate and Color Correct Images for Varying Degrees of Color Blindness

Meenakshi¹,

Singla²

2022

ECS Trans.

View full text Add to dashboard Cite

show abstract

“…The observation shows that subjective feedback is elicited on the compensated images from the colour blind or simulation is done on the compensated images and feedback from normal vision users is sought [31][32][33][34][35]. Other authors have compared the compensated images with the state-of-the-art and checked the effectiveness in terms of contrast, clarity and computation time [36][37][38][39][40]. A couple of authors have used Thurstone's Law of Comparative Judgment for seeking subjective feedback from the colour blind on the compensated images [41][42].…”

Section: Review Of Existing Literaturementioning

confidence: 99%

A novel image quality assessment method and coefficient of quality for digital solutions of colour blindness

Swaminathan

Singla

2021

IET Image Processing

View full text Add to dashboard Cite

Eyesight is one of the primary senses that human beings have. Reports show that colour blindness, a form of colour vision deficiency (CVD), affects about 8% of the male population and 0.5% of female population. The Assistive Technology Act of 2004 lays focus on technologies that help individuals with disabilities and deficiencies. With the rapid advancement in technologies, several assistive solutions are available for visually impaired or CVD patients. Such solutions involve simulation and compensation of conflicting colours to help the colour blind in the visual perception of colours. Given the increased usage of the web, post the pandemic, these solutions improve the quality of life for the colour blind. Defining the image quality assessment criteria for such digital solutions becomes imperative. The study proposes a novel method for image quality assessment of digital solutions aimed at assisting the colour blind users. The proposed coefficient of quality (CQ) would be useful to rank colour compensation and recolouring algorithms. Experiments were conducted with a novel questionnaire set designed for this quality measurement. The results affirm the efficiency of the assessment method proposed. This will also provide objective feedback to the researchers and experts in this area to improve their solutions for CVD patients.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

show abstract

“…Currently, most color adaptation algorithms are based on color mapping, i.e., they map some colors onto other colors, as it the case of the following algorithms due to Martin et al [7], Ichikawa et al [8], Rasche et al [9], Iaccarino et al [10], Huang et al [11], Kuhn et al [12], Doliotis et al [13], Wang et al [14], Chen et al [15], and Ribeiro and Gomes [16] [17]. However, in general, these algorithms tend to recoloring most pixels of an image, causing loss of naturalness of color as perceived by dichromat people [Ichikawa et al 2003 [Flatla et al 2013], though the resulting contrast is more noticeable after all.…”

Section: B Related Workmentioning

confidence: 99%

Contour Enhancement Algorithm for Improving Visual Perception of Deutan and Protan Dichromats

Ribeiro¹,

Gomes²

2019

IJIMAI

View full text Add to dashboard Cite

A variety of recoloring methods has been proposed in the literature to remedy the problem of confusing redgreen colors faced by dichromat people (as well by other color-blinded people). The common strategy to mitigate this problem is to remap colors to other colors. But, it is clear this does not guarantee neither the necessary contrast to distinguish the elements of an image, nor the naturalness of colors learnt from past experience of each individual. In other words, the individual's perceptual learning may not hold under color remapping. With this in mind, we introduce the first algorithm primarily focused on the enhancement of object contours in still images, instead of recoloring the pixels of the regions bounded by such contours. This is particularly adequate to increase contrast in images where we find adjacent regions that are color-indistinguishable from the dichromacy's point of view.

show abstract

A skillet-based recoloring algorithm for dichromats

Cited by 12 publications

References 24 publications

A Fuzzy Based Method to Simulate and Color Correct Images for Varying Degrees of Color Blindness

A Fuzzy Based Method to Simulate and Color Correct Images for Varying Degrees of Color Blindness

A novel image quality assessment method and coefficient of quality for digital solutions of colour blindness

Contour Enhancement Algorithm for Improving Visual Perception of Deutan and Protan Dichromats

Contact Info

Product

Resources

About