Color Processing Research Articles

Research on the detection and recognition system of target vehicles based on fusion algorithm

<p>In modern society, the monitoring of vehicles is paramount for upholding traffic safety and order. This paper delves into a Graphical User Interface (GUI)-driven system for vehicle target detection and integration. This system seamlessly integrates three pivotal functionalities: vehicle type recognition, license plate recognition, and driver face recognition. It automates the vehicle inspection assessment process through an intuitive user interface. Specifically, for license plate recognition, the system leverages traditional computer vision techniques, including color and grayscale processing, radon transform, morphological operations, edge detection, character segmentation, and character recognition. The driver face recognition module incorporates methods such as image gray scaling, Gaussian filtering for denoising, face detection, and feature extraction. Meanwhile, vehicle type recognition is achieved by extracting Histogram of Oriented Gradients (HOG) features and utilizing a Support Vector Machine (SVM) classifier. Experimental findings highlight the system’s remarkable recognition accuracy, offering a highly efficient and dependable solution for the automated inspections of vehicles.</p>

Motion-guided semantic alignment for line art animation colorization

Line art animation colorization aims to colorize a sequence of line art frames with a reference while ensuring semantic alignment across frames. Recent methods have utilized similarity metrics to maintain inter-frame semantic alignment. However, these approaches typically struggle with precise pixel-to-pixel motion alignment, resulting in issues like semantic inconsistencies and color blurring. To address these problems, we introduce an innovative Motion-Guided Colorization Network(MGC-Net), which incorporates line art motions into account for achieving coarse to fine semantic alignment. At the coarse level, our approach includes a Hierarchical Cost-feature Distillation (HCD) module. This module is designed to establish accurate pixel-to-pixel motion alignment between frames. It employs a motion distillation loss, which effectively transfers accurate color motion representation to line arts at varying hierarchical levels. Specifically, we utilize the cost features in inter-frames as a representation of motion, processed through our self-supervision operator. At the finer level, we propose the Correlation Refinement (CR) module. This module enhances semantic alignment by integrating semantic contextual dependencies between the color reference and the motion-based reference obtained from our motion-based confidence estimation block. CR module refines the final colorization process, improving clear color detail and semantic consistency across frames. Quantitative and qualitative experiments on animation datasets show that MGC-Net outperforms the state-of-the-art methods.

SwinTExCo: Exemplar-based video colorization using Swin Transformer

Video colorization represents a compelling domain within the field of Computer Vision. The traditional approach in this field relies on Convolutional Neural Networks (CNNs) to extract features from each video frame and employs a recurrent network to learn information between video frames. While demonstrating considerable success in colorization, most traditional CNNs suffer from a limited receptive field size, capturing local information within a fixed-sized window. Consequently, they struggle to directly grasp long-range dependencies or pixel relationships that span large image or video frame areas. To address this limitation, recent advancements in the field have leveraged Vision Transformer (ViT) and their variants to enhance performance. This article introduces Swin Transformer Exemplar-based Video Colorization (SwinTExCo), an end-to-end model for the video colorization process that incorporates the Swin Transformer architecture as the backbone. The experimental results demonstrate that our proposed method outperforms many other state-of-the-art methods in both quantitative and qualitative metrics. The achievements of this research have significant implications for the domain of documentary and history video restoration, contributing to the broader goal of preserving cultural heritage and facilitating a deeper understanding of historical events through enhanced audiovisual materials.

The underlying molecular mechanisms of hormonal regulation of fruit color in fruit-bearing plants.

Fruit color is a key feature of fruit quality, primarily influenced by anthocyanin or carotenoid accumulation or chlorophyll degradation. Adapting the pigment content is crucial to improve the fruit's nutritional and commercial value. Genetic factors along with other environmental components (i.e., light, temperature, nutrition, etc.) regulate fruit coloration. The fruit coloration process is influenced by plant hormones, which alsoplay a vital role in various physiological and biochemical metabolic processes. Additionally, phytohormones play a role in the regulation of a highly conserved transcription factor complex, called MBW (MYB-bHLH-WD40). The MBW complex, which consists of myeloblastosis (MYB), basic helix-loop-helix (bHLH), and WD40 repeat (WDR) proteins, coordinates the expression of downstream structural genes associated with anthocyanin formation. In fruit production, the application of plant hormones may be important for promoting coloration. However, concerns such as improper concentration or application time must be addressed. This article explores the molecular processes underlying pigment formation and how they are influenced by various plant hormones. The ABA, jasmonate, and brassinosteroid increase anthocyanin and carotenoid formation, but ethylene, auxin, cytokinin, and gibberellin have positive as well as negative effects on anthocyanin formation. This article establishes the necessary groundwork for future studies into the molecular mechanisms of plant hormones regulating fruit color, ultimately aiding in their effective and scientific application towards fruit coloration.

Environmental Sustainability Analysis of Rotary-Screen Printing and Digital Textile Printing

Worldwide concern regarding the need for more sustainable textile supply chain prompted emphasis on innovation in the coloration process, often considered the most problematic segment of the supply chain. Digital textile printing, an emerging coloration technology, has the potential to improve sustainability significantly. This study undertakes an environmental sustainability analysis that compares the impacts of rotary-screen printing, the traditional, more established printing method, and digital textile printing. Researchers partnered with Creditex S.A.A., a vertically integrated textile company from Peru, to perform the research in a realistic factory setting. Creditex printed a 16-color design for an order of 1000m cotton fabric with reactive dye occupying both rotary-screen printing and digital textile printing and collected environmental impact data throughout the production process, including consumption, usage, and wastage. The findings suggest that digital textile printing is favorable to rotary-screen printing in terms of environmental sustainability impacts within the research context.

Asymmetric distribution of color-opponent response types across mouse visual cortex supports superior color vision in the sky.

Color is an important visual feature that informs behavior, and the retinal basis for color vision has been studied across various vertebrate species. While many studies have investigated how color information is processed in visual brain areas of primate species, we have limited understanding of how it is organized beyond the retina in other species, including most dichromatic mammals. In this study, we systematically characterized how color is represented in the primary visual cortex (V1) of mice. Using large-scale neuronal recordings and a luminance and color noise stimulus, we found that more than a third of neurons in mouse V1 are color-opponent in their receptive field center, while the receptive field surround predominantly captures luminance contrast. Furthermore, we found that color-opponency is especially pronounced in posterior V1 that encodes the sky, matching the statistics of natural scenes experienced by mice. Using unsupervised clustering, we demonstrate that the asymmetry in color representations across cortex can be explained by an uneven distribution of green-On/UV-Off color-opponent response types that are represented in the upper visual field. Finally, a simple model with natural scene-inspired parametric stimuli shows that green-On/UV-Off color-opponent response types may enhance the detection of 'predatory'-like dark UV-objects in noisy daylight scenes. The results from this study highlight the relevance of color processing in the mouse visual system and contribute to our understanding of how color information is organized in the visual hierarchy across species.

Improved coloration of hemp fabrics via low-pressure argon plasma assisted surface modification

Interest in hemp as a viable cellulosic fibre for clothing has increased, driven partly by its economic benefits and the importance of natural renewable materials in emerging circular economies. However, the coloration and chemical finishing of lignocellulosic fibres such as hemp typically require large quantities of water and chemicals. Argon plasma pretreatment provides a way of modulating the physical properties of hemp fibres to improve the coloration process without compromising other bulk properties such as tensile strength. Such plasma treatments may contribute to alleviating the negative environmental impacts associated with liquid pretreatments, heating, or the use of auxiliary chemicals. Dyeing of hemp fibres is particularly challenging due to its crystalline chemical structure. In this study, low-pressure argon plasma-assisted surface modification of woven hemp fabrics up to 600 s at 40 and 80 Hz was explored for enhanced dyeability, resulting in enhanced dye-fibre bonding. Fourier-transform infrared spectroscopy and Raman spectroscopy of argon plasma pretreated hemp fabrics produced no noticeable changes in the functional groups of the fibres, but a physiochemical modification was observed in terms of the density of polar groups. Scanning electron microscopy (SEM) images revealed marked morphological changes including nano-etching of the fibre surface at certain argon plasma process conditions. The pretreatment process increased fibre hydrophilicity, and enhanced reactivity of the surficial –OH groups towards fibre-reactive and vat dyes, resulting in higher colour strength in dyed woven hemp fabrics. Overall, we envisage such plasma pretreatments may impact positively on the material and energy efficiency of the hemp fabric dyeing process.

A circuit motif for color in the human foveal retina

The neural pathways that start human color vision begin in the complex synaptic network of the foveal retina where signals originating in long (L), middle (M), and short (S) wavelength-sensitive cone photoreceptor types are compared through antagonistic interactions, referred to as opponency. In nonhuman primates, two cone opponent pathways are well established: an L vs. M cone circuit linked to the midget ganglion cell type, often called the red-green pathway, and an S vs. L + M cone circuit linked to the small bistratified ganglion cell type, often called the blue-yellow pathway. These pathways have been taken to correspond in human vision to cardinal directions in a trichromatic color space, providing the parallel inputs to higher-level color processing. Yet linking cone opponency in the nonhuman primate retina to color mechanisms in human vision has proven particularly difficult. Here, we apply connectomic reconstruction to the human foveal retina to trace parallel excitatory synaptic outputs from the S-ON (or "blue-cone") bipolar cell to the small bistratified cell and two additional ganglion cell types: a large bistratified ganglion cell and a subpopulation of ON-midget ganglion cells, whose synaptic connections suggest a significant and unique role in color vision. These two ganglion cell types are postsynaptic to both S-ON and L vs. M opponent midget bipolar cells and thus define excitatory pathways in the foveal retina that merge the cardinal red-green and blue-yellow circuits, with the potential for trichromatic cone opponency at the first stage of human vision.

Ionic conductivity and dielectric characteristics of a Li incorporated PVA electrolyte membrane and a study of a fully solid-state electrochromic device based on it

The construction and study of a fully solid state electrochromic (EC) device with cathodic coloration exhibiting very fast response times (< 1s) is reported using a WO3 EC layer and a poly (vinyl alcohol) (PVA)- Lithium acetate membrane electrolyte. Broadband dielectric studies on the polymer membranes with different Li concentrations show multiple relaxation mechanisms out of which a segmental relaxation prominent beyond a certain composition is strongly correlated with Li-ion conduction yielding better ionic conductivity and reversible coloration in the EC device. The relatively high Li conductivity in PVA has a direct correspondence with the lowering of the crystallinity of PVA and a decrease of the glass transition temperature, Tg with increasing Li addition. A simple model of the coloration process suggests that the short electrolyte diffusion length coupled with a high electric field and an interfacial emf that varies as ≈t−0.6 results in the swift current response of the film with an optimal performance at 20 wt.% Li in PVA, exceeding which irreversible coloration can occur on the surface. The transient current is crucial for the observed swift switching characteristics. Ageing studies for almost a month indicate potential stability of the EC device for over 150 cycles.

Mapping Ocean Gateways from 3D Seismic Data Using Color Processing and Analogues from Seismic Data

Mapping sedimentary features to delineate ancient ocean gateways from 3D seismic data has long been a challenge due to their limited vertical resolution. We present the technique of color processing of seismic data which improves the vertical resolution to very few seismic samples corresponding to 5–10 m. The result is a representation of the seismic impedance contrast correlation in Red-Green-Blue (RGB) colors, which creates images similar to satellite images that assist the geological interpretation because the RGB colors can be associated with mud-rich and sand-rich sediments. Using this approach, we have extracted six different sedimentary bedforms from different bottom flow settings and correlated these with the bedform-velocity matrix by Stow et al. (2009). Then we studied bedform assemblies in their regional context for the area covered by the 3D seismic data set. We conclude with comparing a modern and an ancient analogue – both from 3D seismic data – and infer paleo flow direction and velocity using oceanographic measurements available for the modern analogue. The method provides insights into ocean bottom currents and their impact on the formation of contourite depositional systems in modern and ancient ocean gateways which contribute to the reconstruction of the paleoclimate as an input to present day climate change models.

BiSTNet: Semantic Image Prior Guided Bidirectional Temporal Feature Fusion for Deep Exemplar-Based Video Colorization.

How to effectively explore the colors of exemplars and propagate them to colorize each frame is vital for exemplar-based video colorization. In this article, we present a BiSTNet to explore colors of exemplars and utilize them to help video colorization by a bidirectional temporal feature fusion with the guidance of semantic image prior. We first establish the semantic correspondence between each frame and the exemplars in deep feature space to explore color information from exemplars. Then, we develop a simple yet effective bidirectional temporal feature fusion module to propagate the colors of exemplars into each frame and avoid inaccurate alignment. We note that there usually exist color-bleeding artifacts around the boundaries of important objects in videos. To overcome this problem, we develop a mixed expert block to extract semantic information for modeling the object boundaries of frames so that the semantic image prior can better guide the colorization process. In addition, we develop a multi-scale refinement block to progressively colorize frames in a coarse-to-fine manner. Extensive experimental results demonstrate that the proposed BiSTNet performs favorably against state-of-the-art methods on the benchmark datasets and real-world scenes. Moreover, the BiSTNet obtains one champion in NTIRE 2023 video colorization challenge (Kang et al. 2023).

Exploiting Turmeric’s Coloring Capability to Develop a Functional Pigment for Wood Paints: Sustainable Coloring Process of Polyamide 11 Powders and Their Strengthening Performance

Currently, the wood coatings industry is focusing on creating unique, vibrant finishes using new functional pigments. Simultaneously, there is a growing adoption of eco-friendly bio-based materials, reflecting trends in other sectors and supporting the circular economy. Thus, the aim of this study is to unveil a straightforward, cost-effective, and notably sustainable process for exploiting the coloring potential of turmeric powder and coloring polyamide 11-based fillers, employed as multifunctional pigments for wood coatings. Through the incorporation of this additive into a wood paint, the study demonstrates its dual effect of enhancing the aesthetics of the final composite layer while leveraging the beneficial protective properties inherent to polyamide 11. The impact of these additives on sample aesthetics is assessed through optical observations, as well as measurements of color, gloss, and surface roughness. The strengthening contribution of the functional pigment is evaluated using the Taber abrasion resistance test, static friction coefficient measurements, and Buchholz surface hardness test. Finally, the aesthetic consistency of the bio-based filler and the coloring efficiency of the sustainable process are tested by subjecting the samples to aggressive conditions, including the UV-B chamber exposure test, cold liquids resistance tests, and water uptake test. Ultimately, the study illustrates how this functional bio-based pigment not only provides sufficient protection but also meets current eco-requirements, thereby contributing to the sustainability of the wood coatings industry.

Continual few-shot patch-based learning for anime-style colorization

The automatic colorization of anime line drawings is a challenging problem in production pipelines. Recent advances in deep neural networks have addressed this problem; however, collectingmany images of colorization targets in novel anime work before the colorization process starts leads to chicken-and-egg problems and has become an obstacle to using them in production pipelines. To overcome this obstacle, we propose a new patch-based learning method for few-shot anime-style colorization. The learning method adopts an efficient patch sampling technique with position embedding according to the characteristics of anime line drawings. We also present a continuous learning strategy that continuously updates our colorization model using new samples colorized by human artists. The advantage of our method is that it can learn our colorization model from scratch or pre-trained weights using only a few pre- and post-colorized line drawings that are created by artists in their usual colorization work. Therefore, our method can be easily incorporated within existing production pipelines. We quantitatively demonstrate that our colorizationmethod outperforms state-of-the-art methods.

Deficits of the "Good" Eye in Amblyopia: Processing Geometric Properties.

Although fellow eyes of amblyopia are typically considered normal, recent studies have revealed impairments in certain aspects of vision. However, it remains unclear at which level of object processing these impairments occur. This study aims to investigate the functional level of visual perception impairment in the fellow eye of children and adults with amblyopia using the geometric functional hierarchy discrimination task based on Klein Mathematics methodology. Seventy-six patients with amblyopia (40 children and 36 adults) and 77 age-matched healthy controls (40 children and 37 adults) were recruited for this study. The participants completed four sets of geometric hierarchies (in ascending order of stability: Euclidean, affine, projective, and topology) and one set of color discrimination tasks. They were instructed to rapidly and accurately select a distinct shape from the four quadrants. The participants' performance was evaluated using the inverse efficiency (IE) score (IE = response time (RT)/accuracy). The results of IEs show that the fellow eye of children with amblyopia exhibits normal topological processing, yet displays higher IEs in other geometric properties and color processing, suggesting impairments in these specific discrimination abilities. However, adults with amblyopia did not show deficits on any discrimination types compared with adult controls. The lack of compromised topological processing suggests that amblyopia may not have inflicted any damage to the subcortical visual pathways. Furthermore, these deficits observed in the fellow eye tend to diminish significantly during adulthood, implying that amblyopia may potentially hinder the maturation process of the fellow eye.

Low luminance contrast’s effect on the color appearance of S-cone patterns

There is a surprisingly strong effect on color appearance when low levels of luminance contrast are added to visual targets in which only S-cones are modulated. This phenomenon can be studied with checkerboard patterns composed of alternating S-cone-modulated checks and gray checks. + S checks look purple when surrounded by slightly brighter gray checks but look highly desaturated (lavender, almost white) when surrounded by darker gray checks. −S checks change in hue with luminance contrast; they look yellow when surrounded by darker gray checks but are greener when surrounded by lighter checks. Psychophysical paired comparisons confirm these perceptions. Furthermore, visual evoked potentials (VEPs) recorded from human posterior cortex indicate that signals evoked by low luminance contrast interact nonlinearly with S-cone-evoked signals in early cortical color processing. Our new psychophysics and electrophysiology results prove that human perception of color appearance is not based on neural computations within a separate, isolated color system. Rather, signals evoked by color contrast and luminance contrast interact to produce the colors we see.

Photochromic ionogel with a wide temperature range and fatigue resistance for high-resolution rewritable information record

Recently, photochromic hydrogels have received significant attention and hold substantial promise for rewritable information record. However, the intrinsic instability of hydrogels has restricted their applications. Herein, a photochromic ionogel aiming at extending service life for long-term use is presented by embedding photochromic ammonium molybdate tetrahydrate [(NH4)6Mo7O24·4H2O] (Mo7) in engineered double networks. Covalently cross-linked 2-hydroxyethyl acrylate (HEA) and self-assembled cationic cellulose (JR-400) constitute the networks, and a protic ionic liquid of ethylammonium nitrate (EAN) is immobilized therein. Such a design affords the ionogel comprehensive properties, including high optical transparency (>97%), good adhesion, anti-dehydration, wide operating temperature range (–60 to 150 °C) as well as the sensitive and stable UV-light responsiveness (within 30 s). Besides, the ionogel exhibits admirable mechanical properties of high toughness (over 180 kJ/m3), excellent resilience and a high fatigue threshold (over 1000 cycles with negligible hysteresis). The photochromic process is typically accomplished by photoreduction of Mo7, which is combined with network through electrostatic interaction with quaternized JR-400. The distinctive feature is that EAN serving as both proton donor and electron donor, plays a dominant role in coloration process and formation of charge-transfer complex. The photochromic mechanism which is less well understood in ionic liquid medium, has been revealed. Remarkably, the ionogel used as an information carrier exhibits outstanding stability in a wide operating temperature range. The superiorities of the photochromic ionogel including accurate information recording capacity and application in harsh environments have greatly boosted the high-quality information dissemination and expanded applications of photochromic soft materials.

Color Plates, Material, and Condition: Hermann Krone’s Contributions to Lippmann Interferential Color Photography

Abstract Lippmann color photographs are among the rarest examples of early color photography in public and private collections worldwide. At the time, Hermann Krone was probably one of those who contributed most actively and with remarkable results to the Lippmann process. After general remarks about Krone’s work, this paper will describe more deeply his book about color photography focusing on the direct color process, the technology he practiced himself to accomplish interferential color, and the body of his Lippmann color photographs, which still exists today in major collections, and which has been recently examined by the author. With a focus on the work of Krone, the paper aims to give an overview of the variety of presentation forms of Lippmann color images in existence today and closes with information on the permanence and preservation of these early color photographic materials.

Colorimetric characterization of multispectral imaging systems for visualization of historical artifacts

Multispectral imaging has long been used in the study of cultural heritage artifacts, particularly manuscripts with low-contrast text. The goal of multispectral imaging systems has largely been to enhance the text by imaging outside the spectral response of the human visual system and by applying various image processing techniques. However, there is a desire to use multispectral images for high quality, true color rendering of the artifacts as well. We use two multispectral imaging systems in this work. One of them is the Multispectral Imaging System for the study of Historical Artifacts (MISHA) which has been demonstrated to have significant utility at a lower cost and better ease of use compared to commercially available systems. This system was specifically designed and built for the purpose of imaging artifacts, particularly manuscripts and works on paper with illegible text due to deterioration and other environmental causes. Given this goal of “discovering” low-contrast text (and other features) on planar objects, the system has not been optimized for color reproduction purposes. The second system is a commercially available MegaVision EVTM Spectral Imaging System. This system is also used for cultural heritage imaging. In this work, we develop an approach to colorimetrically characterize these cameras and illumination systems, adding an option for accurate color reproduction to their capabilities. To do this, we present two different approaches. The first approach we call the Color Transformation Method. Here we use a Macbeth ColorChecker to first linearize the camera photometric response, and then find a linear matrix transformation from the camera response to CIEXYZ tristimulus values. The second approach we call the Illuminant Method. Here we consider each output by the camera as a reflectance factor value at the known wavelength of a narrowband illuminator. We then convert these values to the color of the object in terms of CIEXYZ tristimulus values. We show that the Color Transformation Method using a Macbeth ColorChecker leads to a more accurate result. Meanwhile, the Illuminant Method is much simpler and produces acceptable results, particularly considering accurate color reproduction was not a goal in designing the MISHA camera system. The same methods are applied to both imaging systems to show the robustness and applicability of the approaches developed herein to other imaging systems. Results are shown for both quantitative calibration targets as well as artifacts of interest to the field of cultural heritage studies. It is worth noting that we are not comparing the two imaging systems overall or the color processing software available from MegaVision. Rather, we simply show that the two approaches developed here are applicable to different multispectral imaging systems, from a very cost-effective system, i.e., MISHA to a more expensive one, i.e., MegaVision.

Shadow-aware image colorization

Significant advancements have been made in colorization in recent years, especially with the introduction of deep learning technology. However, challenges remain in accurately colorizing images under certain lighting conditions, such as shadow. Shadows often cause distortions and inaccuracies in object recognition and visual data interpretation, impacting the reliability and effectiveness of colorization techniques. These problems often lead to unsaturated colors in shadowed images and incorrect colorization of shadows as objects. Our research proposes the first shadow-aware image colorization method, addressing two key challenges that previous studies have overlooked: integrating shadow information with general semantic understanding and preserving saturated colors while accurately colorizing shadow areas. To tackle these challenges, we develop a dual-branch shadow-aware colorization network. Additionally, we introduce our shadow-aware block, an innovative mechanism that seamlessly integrates shadow-specific information into the colorization process, distinguishing between shadow and non-shadow areas. This research significantly improves the accuracy and realism of image colorization, particularly in shadow scenarios, thereby enhancing the practical application of colorization in real-world scenarios.

THE IMPACT OF MOVIE COLORIZATION BY ARTIFICIAL INTELLIGENCE ON CINEMATIC SYMBOLISM: A CASE STUDY OF SATYAJIT RAY’S ‘PATHER PANCHALI’

The objective of image colorization is to add color to a monochrome input picture to generate a colorful outcome, which is a classic and essential issue in visual effects. In cinema, color has a significant role in on various levels. But it was not the fundamental component of cinema. Although color was added in film later, but for a long time people were used to watching movies on their black and white television set.This study depends on the effort of a Bengali professor based in the United States who used artificial intelligence to colorize Satyajit Ray’s ‘Pather Panchali’ as a quarantine experiment. This research analyzes the use of colorization in ‘Pather Panchali’ to determine whether the colors work well to emphasize the film's symbolic meaning. It also examines whether there is still a place for sentimentality after colorization and how well AI works at coloring in black and white movies.The research objectives include evaluating the role that colorization plays in bringing the film's meaning to light with regard to certain situations, examining among specialists the nostalgia/emotions linked with classic black and white films, and gauging experts reaction to the practice of using AI to colorize previously black-and-white movies. This study uses in-depth interviews as a qualitative research approach for gathering expert opinions.This study concludes that the cinematic symbolism of the black and white version of ‘Pather Panchali’ is lost in the colorized version. Expert interviews revealed the complex connection between colorization and the film's visual style. The findings emphasize the need for careful consideration and preservation of the original black-and-white format, while also recognizing the advancements and limitations of artificial intelligence in the colorization process.