Color vision deficiency represents an inability to perceive differences between certain colors that can be distinguished in the case of regular color vision. This article proposes a new daltonization method for re-coloring image segments perceived as confusingly colored by color deficient observers and, thus, to improve their perceived image quality. The idea behind this approach is that only one image color center should be located on one confusion line. If colors of two or more segments lie on the same confusion line, then they should be remapped in a direction perpendicular to the confusion line taking into account the image content—the color distribution of other segments. The method conserves the image naturalness by restricting, for each segment center, an area of admissible remapping. This achieves re-coloring balance where colors are made sufficiently distinguishable from each other, but they do not deviate too much from the original image colors. The proposed re-coloring concept is applicable to all types of dichromacy and anomalous trichromacy with adjustment for their set of confusion lines. The simulation results show that the re-coloring converts an original image to a version with improved color distinction, confirmed by evaluations of eight color deficient users. An intentionally chosen example demonstrates when and why the proposed method performs better against content-independent methods. Furthermore, results and subjective evaluations indicate that the method provides more natural re-coloring results for anomalous trichromats than in the case of content-dependent methods optimized for dichromats.

This paper presents experimental usage of updated control methods such as thermovision and spectrophotometric analysis in graphic industry. These methods were applied to research the influence of ink volume and material characteristics...

Contemporary media entail colour-coded information. While an average viewer takes colour images for granted, individuals with colour vision deficiency have difficulties in discriminating certain colour combinations and, consequently, have difficulties in perceiving image features. Well-established simulation tools allow us to see the image from their perspective that goes beyond the stereotypical inability to tell red from green by affecting the perception of the entire spectrum. Daltonization methods utilise these simulations to enhance the perceptual image quality for the target population. The paper presents a new concept of daltonization based on finding the optimal choice of discernible colour bins for each image. Similar to other contentdependent methods, the used remapping balances between colour contrast enhancement and naturalness preservation. By providing type and severity of the deficiency and the preferable contrast-naturalness balance and as input parameters, the method can be customized for a particular colour deficient individual.

In this paper, white pixel percentage (WPP) value, as an overall measure of fold crack damages, has been analysed with respect to selected parameters of sample preparation and digitalization process, as well as the results of residual tensile strength. The WPP values were derived by an automated image processing algorithm, developed earlier, based on extensive comparative analysis of the existing computer-aided methods. Results indicate that WPP values correlate well with the extent of fold cracks on the coated samples, as far as the used parameters of sample preparation and digitalization are concerned. In the case of correlation with residual tensile strength, results for samples folded in cross direction revealed that the extent of the visually registered fold cracks agree well with the actual damage, while for samples folded in machine direction, the overall strength losses weren’t alarming, although the fold cracks were detected correctly. In addition, results pointed out that the simplest sample placement position (inner angle of 180°) is not applicable for realistic sample representation. Furthermore, scanners could provide a superior image quality in lab conditions, but for industry application, a camera-based solution would be more purposeful, while micrographs are more suitable for traditional visual analysis.