Color Contrast Research Articles

Application of interlayer perforation and installation of transparent elements in the technology of duplicated decorative polymer films

Objectives. To develop technologies for producing multilayer films of transparent thermoplastic polymers; to study methods of modifying their supramolecular structure; and to determine their optical properties by means of optical-polarization methods for the use of modified films as decorative and design materials in modern architecture.Methods. Industrial samples of polystyrene, low-density polyethylene, polypropylene, and polyvinyl chloride films from various manufacturers (Don Polimer, Vektor, and Sibur) were the objects of the study. The optical properties of the films were studied by means polarized-light spectrophotometry. In order to modify the supramolecular structure of the polymers, the surfaces of the films were treated under isometric conditions with volatile solvents or their aqueous solutions. Parts of the layers of multilayer films were removed by cutting with a punching knife using a press or with a manual device for perforating printing materials.Results. The spectral characteristics of multilayer films of several transparent thermoplastic polymers in polarized light were determined. The study showed that a wide palette of colors and contrasting images can be obtained by mechanically removing part of the layers of multilayer films. The phenomenon of pseudo-disappearance of the outermost layer was discovered after treatment of a stack of films under isometric conditions with volatile solvents or their aqueous solutions.Conclusions. Based on the example of large-scale production thermoplastics, it was shown that a combination of technological methods of stacking, perforation, and local plasticization of films of transparent thermoplastic polymers can produce pleochroic multicolor materials for a range of human activities. The possibility of hidden coding of information on multilayer packaging materials, and its visualization and instrumental reading in polarized light was confirmed by color differential and contrast of 150 and 60 units, respectively. It was also shown that several monochrome tones of different lightness and brightness can be obtained by varying the number of layers or perforating the films in multilayer materials.

Identifying images in the biology literature that are problematic for people with a color-vision deficiency.

To help maximize the impact of scientific journal articles, authors must ensure that article figures are accessible to people with color-vision deficiencies (CVDs), which affect up to 8% of males and 0.5% of females. We evaluated images published in biology- and medicine-oriented research articles between 2012 and 2022. Most included at least one color contrast that could be problematic for people with deuteranopia ('deuteranopes'), the most common form of CVD. However, spatial distances and within-image labels frequently mitigated potential problems. Initially, we reviewed 4964 images from eLife, comparing each against a simulated version that approximated how it might appear to deuteranopes. We identified 636 (12.8%) images that we determined would be difficult for deuteranopes to interpret. Our findings suggest that the frequency of this problem has decreased over time and that articles from cell-oriented disciplines were most often problematic. We used machine learning to automate the identification of problematic images. For a hold-out test set from eLife (n=879), a convolutional neural network classified the images with an area under the precision-recall curve of 0.75. The same network classified images from PubMed Central (n=1191) with an area under the precision-recall curve of 0.39. We created a Web application (https://bioapps.byu.edu/colorblind_image_tester); users can upload images, view simulated versions, and obtain predictions. Our findings shed new light on the frequency and nature of scientific images that may be problematic for deuteranopes and motivate additional efforts to increase accessibility.

Visual Interpretation of High-Resolution Aerial Imagery: A Tool for Land Managers

Abstract Remotely sensed imagery from various collection platforms (e.g., satellites, crewed and uncrewed aircraft) are used by biologists and other conservation personnel to support management activities ranging from monitoring invasive species to assessing land cover and vegetation characteristics. Although remote sensing–based vegetation indices and models have been developed and used for some management applications, straightforward visual interpretation of imagery by on-the-ground personnel may be a pragmatic approach for obtaining time-sensitive and spatially relevant information to support and guide local management activities. Our primary objective was to qualitatively assess our ability to identify patches of target invasive plant species based on simple visual interpretation of high-resolution aerial imagery. We also sought to compare the high-resolution imagery to widely available imagery (e.g., National Agriculture Imagery Program) to determine the efficacy of each for assessing vegetation communities and land-cover features in support of management activities. To accomplish these objectives, we obtained high-resolution imagery and visually scanned and assessed the imagery by using standard geographic information system software. We were able to differentiate patches of crownvetch Securigera varia (L.) Lassen and wild parsnip Pastinaca sativa L., but not spotted knapweed Centaurea stoebe L. or leafy spurge Euphorbia esula L. The relative success in identifying these species had a relationship to plant characteristics (e.g., flower color and morphology, height), time of year (phenology), patch size and density, and potentially site characteristics such density of the underlying vegetation (e.g., grasses), substrate color characteristics (i.e., color contrast with flowers), and physical disturbance. Our straightforward, qualitative assessment suggests that visual interpretation of high-resolution imagery, but not some lower-resolution imagery, may be an efficient and effective tool for supporting local invasive species management through activities such as monitoring known patches, identifying undetected infestations, assessing management actions, guiding field work, or prioritizing on-the-ground monitoring activities.

Effect of hydrothermal aging on color stability and translucency of two zirconia generations compared to lithium disilicate ceramics.

An esthetically acceptable ceramic restoration should have optical properties like the teeth and reflect, transmit, and absorb light. The present investigation compared how hydrothermal aging affected the properties of two types of zirconia and lithium disilicate. Thirty rectangular samples (12×14×1 mm) were prepared and sectioned from three different ceramic blocks/blanks (n=10), then assigned into three groups according to the ceramic type: group Z: IPS e.max ZirCAD prime, gradient zirconia (3Y/5Y-TZP); group K: Katana UTML (5Y-TZP); and group E: IPS e.max CAD (lithium disilicate). Color analysis of samples was performed before and after hydrothermal aging (1, 3, and 5 hours) using a spectrophotometer. Color difference (∆E00), translucency parameter (TP00), and contrast ratio (CR) were evaluated. The microstructural analysis was performed using x-ray diffraction (XRD). Data were statistically analyzed at a significance level of P<0.05. A statistically significant variation was observed across means of ∆E00, TP00, and CR at different times. Group Z displayed the highest statistically significant mean ∆E00. Group E demonstrated the greatest statistically significant mean TP00. Group K exhibited the most statistically significant mean CR. Hydrothermal aging significantly affected the optical characteristics of lithium disilicate and zirconia ceramics. The translucency of samples increased with aging.

Underwater image restoration method based on Walsh–Hadamard transform and attenuation coefficient estimation

Abstract Underwater images often exhibit color distortion and low contrast due to the scattering and absorption of light as it travels through water. Changes in lighting conditions further complicate the restoration and enhancement of these images. Improving the quality of underwater images is crucial for advancements in fields such as marine biology research, underwater measurement, and environmental monitoring. This paper proposes an underwater image restoration method based on the Image Formation Model (IFM), utilizing the Walsh–Hadamard transform and attenuation coefficient estimation. Traditional methods rely on dark channel prior and maximum intensity prior to estimate background light (BL) and transmission maps (TMs), often performing poorly in various underwater environments. Our method uses image blur to estimate BL and depth maps and derives three-channel attenuation coefficients using the gray-world theory to obtain a more accurate TM. Experimental results on real underwater images show that our method effectively eliminates color deviation and contrast distortion while preserving image details, significantly outperforming other IFM-based restoration techniques. Compared to the closest competing algorithms, our method achieves better UIQM and UCIQE scores.

Accuracy of a commonly used mobile ophthalmology application's vision assessment tools in measuring five vision assessment parameters.

The use of mobile ophthalmology applications (MOA) is increasing, but many of these tools have not been validated. This study was performed to assess the accuracy of a popular MOA, Eye Handbook, in measuring five commonly-tested vision assessment parameters (distance visual acuity (DVA), near visual acuity (NVA), colour vision testing (CVT), contrast sensitivity (CS), and pupillary distance (PD)) was compared with traditional vision assessment methods (TVAM) [i.e. Snellen chart, Rosenbaum near card, Ishihara, Pelli Robson test, etc.] performed in the eye clinic setting. Prospective crossover clinical trial of 129 patients meeting inclusion criteria. Participants averaged significantly better DVA (p = 0.0008), NVA (p < 0.0001), and CVT (p = 0.0105) in the MOA than the TVAM, but all three MOA assessments were predictive of the TVAM values. CS was significantly better with the MOA (p < 0.0001). Linear regression and Spearman correlation tests were applied to assess the effect of CS on NVA, which showed no clear relationship between the difference in NVA and the difference in CS. PD using the two methods was in agreement with no significant difference (p = 0.2889). The studied MOA offers an effective means of measuring four common vision parameters: DVA, NVA, CVT, and PD. The MOA can potentially be used by eye care providers, health care providers, and patients, both as a screening tool with correction factor and to monitor ocular pathologies. Atypical MOA measurements should prompt testing in the clinic with formal TVAMs.

Retinomorphic Color Perception Based on Opponent Process Enabled by Perovskite Bipolar Photodetectors.

The ability to perceive color by the retina can be attributed to both its trichromatic photoreceptors and the antagonistic neural wiring known as the opponent process. While neuromorphic sensors have been shown to demonstrate memory and adaptation capabilities, color perception is still challenging due to the intrinsic lack of spectral selectivity in narrow bandgap semiconductors. Furthermore, research on emulating neural wiring is severely lacking. The combination of halide perovskite materials with a tunable bandgap and a novel bipolar photodetector design emulates the efficiency of the retina in processing color information. The stimuli-responsive material is also responsible for maintaining partial color constancy-an adaptation feature. Leveraging the unique enhancement of color contrasts, an in-sensor data compression and edge detection can also be demonstrated. The color perception, chromatic adaptation, and color contrast enhancement make perovskite bipolar photodetectors a unique example where the sensor and neural wiring can be co-developed in conjunction.

A robust underwater polarization image recovery based on Angle of Polarization with low-rank and sparse decomposition

Underwater imaging method based on the Angle of Polarization (AoP) is extremely popular due to its ability to remove the backscattered light effectively. However, existing methods overlook a potentially important phenomenon: the AoP contains significant noise in the real world, which leads to inaccurate estimations of key parameters. In this study, we propose a novel robust underwater polarization image recovery method based on AoP with low-rank and sparse decomposition. Based on the analysis of polarization, the AoP of backscattering exhibits low-rank characteristics, whereas the AoP of noise and targets demonstrates sparsity. Considering different sparsity of AoP, we combine Robust Principal Component Analysis and Alternating Direction Multiplier Method (RPCA-ADMM) with an adaptive threshold shrinkage method for low-rank and sparse decomposition, the AoP of the backscattering is obtained. Moreover, according to the low-rank component of the AoP, the Degree of Linear Polarization (DoLP) of backscattering can be effectively and automatically estimated without considering whether the background region exists, relying on a frequency prior strategy. Finally, the degraded image is recovered utilizing underwater polarization imaging model. Extensive experimental results demonstrate that the recovered images from the proposed method have abundant detail, high contrast, and minimal color distortion, which is competitive with most state-of-the-art methods.

Color Maps: Facilitating the Clinical Impact of Quantitative MRI.

Presenting quantitative data using non-standardized color maps potentially results in unrecognized misinterpretation of data. Clinically meaningful color maps should intuitively and inclusively represent data without misleading interpretation. Uniformity of the color gradient for color maps is critically important. Maximal color and lightness contrast, readability for color vision-impaired individuals, and recognizability of the color scheme are highly desirable features. This article describes the use of color maps in five key quantitative MRI techniques: relaxometry, diffusion-weighted imaging (DWI), dynamic contrast-enhanced (DCE)-MRI, MR elastography (MRE), and water-fat MRI. Current display practice of color maps is reviewed and shortcomings against desirable features are highlighted. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 2.

Contrast Sensitivity, Color Discrimination and Visual Acuity as Risk Factors for Visual Dysfunction in Non-Proliferative Diabetic Retinopathy

Contrast Sensitivity, Color Discrimination and Visual Acuity as Risk Factors for Visual Dysfunction in Non-Proliferative Diabetic Retinopathy

Thermochromic Properties of 3C-, 6H- and 4H-SiC Polytypes up to 500°C

The thermochromic properties (color change with temperature) of n type doped SiC wafers of different polytypes (3C, 4H and 6H) have been investigated up to 500°C under air. It was found that 3C-SiC color passes from bright yellow at room temperature to deep orangeat 500°C leading to a color contrast (ΔE) as high as 64. The hexagonal polytypes undergo also a color change upon heating but far less pronounced, with ΔE values &lt;20. All these semiconductors undergo band gap shrinkage upon heating which effect largely participated to the observed color change. This effect is very sensitive for 3C polytypesince its bandgap is already in the visible energy range at room temperature. The thermochromicity of 3C-SiC was found to be reversible thanks to its thermal stability and its resistance towards oxidation.

Phase change polymer-based structural color photonic films for contactless and inkless writing irreversibly

Thermal-responsive photonic crystals (PCs) have attracted considerable interest due to their triggerable and adjustable optical capabilities, which are promising for various applications. However, developing a mechanism for rapid and irreversible structural color transformation in PCs that enables contactless and inkless writing has significant research value. Herein, phase change polymers are incorporated into functional optical platforms capable of rapid and irreversible structural color transformation in response to thermal stimuli. In crystalline state, phase change polymers used as inverse opal scaffolds in photonic films produce structural color with high saturation. The collapse of the highly ordered inverse opal structure, driven by thermal-mediated transformation during the crystalline/amorphous conversion of phase change polymers, is identified as the primary mechanism for achieving rapid and irreversible structural color transformation. These significant color variations between the inverse opal and collapsed structures provide high color contrast and resolution. The photonic films exhibit excellent hydrophobicity, solvent resistance, and storage stability. Additionally, incorporating the photothermal material carbon black (CB) enhances color saturation and imparts efficient photothermal conversion ability to films. By modulating the photothermal effect via near-infrared (NIR) laser light, phase change polymer-based structural color photonic films can achieve a permanent configuration at 42 °C, resulting in high-resolution images. These outstanding features offer a feasible method for next-generation innovative inkless writing and printing.

Tunable optoelectronic performances of aminated benzothiadiazole-based D-A-D conjugated electrochromic polymers

Introducing heteroatom groups into benzothiadiazole (BT) unit has proven to be a very effective way to improve the optoelectronic properties of conjugate polymer due to its comprehensive advantages of lowering the HOMO or LUMO energy level, and increasing the interaction force on the polymer backbone. However, at present, little attention was paid to introducing amino groups into the BT unit. Herein, in this work, three D-A-D type aminated monomers (Th–NH2-BT, Th–2NH2-BT, and EDOT-2NH2-BT) with aminated benzothiadiazole as the acceptor unit and thiophene or 3,4-ethylenedioxythiophene (EDOT) as the donor unit were successfully synthesized by Stille coupling reaction, and their corresponding aminated polymers (P(Th–NH2-BT), P(Th–2NH2-BT), and P(EDOT-2NH2-BT)) were facilely achieved by electrochemical polymerization method. The optoelectronic properties of the aminated monomers and their D-A polymers were carefully analyzed, and the electrochemical and electrochromic properties of the resultant aminated polymers were further studied. The finally results show that the absorption and fluorescence spectra of Th–2NH2-BT and EDOT-2NH2-BT are both blue-shifted compared to Th–NH2-BT, and the corresponding optical bandgap are gradually increased (2.41 eV–2.65 eV). EDOT-2NH2-BT has a relatively lower oxidation potential (0.73 V) and P(EDOT-2NH2-BT) also has a wide potential window and better redox stability, which was very beneficial for improving its resultant D-A aminated polymers’ optoelectronic properties. As a result, as-formed P(EDOT-2NH2-BT) shown obvious color change from green in the neutral state to gray in the oxidized state with favorable electrochromic performances, with a high optical contrast (ΔT = 17.17 % at 860 nm) and high coloration efficiency (CE = 223 C−1 cm2 at 860 nm), so it is one of the promising materials that can be used in electrochromic devices.

Bismuth Oxychloride Nanoflakes Based Wearable Colorimetric Sensors for Efficient Monitoring of UV Exposure

Ultraviolet radiation from sunlight is essential for human health in many ways such as facilitating vitamin D synthesis while excessive exposure can cause adverse effects such as premature aging, sunburn, and skin cancers. In the USA, between 2007 and 2011, nearly five million adults were treated for skin cancer annually with average treatment costs of $8.1 billion each year. Hence, monitoring daily exposure to sunlight is essential to avoid developing health risks. Colorimetric UV sensors change color as a function of UV exposure, provide onsite information about the level of exposure, and can act as a personal wearable device to assist in making informed decisions on sunlight exposure. These sensors utilize radiation-induced reactions on a dye to produce a color change. We developed a BiOCl based wearable UV sensor for monitoring UV exposure where a white-to-black color transformation is induced due to the creation of oxygen vacancies in BiOCl. This color transformation is not quantifiable in bulk BiOCl; hence BiOCl was purposely dispersed on filter paper to form petal-like nanostructures that help quantify the color change. Four different dye molecules, 6-carboxyfluorescein, 5-carboxyfluorescein, rhodamine-B, and Prussian blue were evaluated, where 6-carboxyfluorescein gave the best color contrast. The sensor responds to UVA, UVB, and UVC and with proper UV filters can be made selective for specific UV radiations. This unique colorimetric UV sensor can help manage personal UV exposure and reduce the risk of sun exposure ailments.Reference: Kyle Troche, Kannan Ramaiyan, Timothy J. Boyle, Fernando H. Garzon, “Bismuth Oxychloride Nanoflakes Enabled High Sensitivity Colorimetric UV Dosimetry” ACS Appl. Nano. Mater. 2023, 6, 7.

Bornean Orangutan Nest Classification using Image Enhancement with Convolutional Neural Network and Kernel Multi Support Vector Machine Classifier

Preserving wildlife habitats is crucial in mitigating climate change. Species like orangutans and monkeys contribute to fruiting and planting in forests. The World Wide Fund Sabah Malaysia faces challenges in manually identifying and classifying orangutan nests for studying their behaviour and conserving their habitats. To address this, we propose automating the classification of captured images using machine learning algorithms. This research involves three key components: image processing, feature extraction, and image classification. Our proposed image processing includes several steps, such as image pre-processing and enhancement techniques like local contrast enhancement, sharpening, intensity adjustment, histogram equalization, and colour thresholding. We applied four different Convolutional Neural Networks (CNNs) to extract and identify orangutan nests’ features. Subsequently, we utilize Support Vector Machine (SVM) for image classification. The results reveal that the Inception Residual Network Version 2 (ResNet-v2) achieves the best performance. This architecture is then combined with a kernel SVM to classify Bornean orangutan nests. Our approach demonstrates impressive results, boasting an accuracy of 96.60%, an F1-score of 96.60%, a precision of 96.59%, and a recall of 96.58%. These metrics underscore the high accuracy and effectiveness of our proposed methodology for classifying Bornean orangutan nests. By reducing the need for extensive human intervention in image analysis, our method presents a valuable tool for conservationists and researchers committed to studying and safeguarding these endangered orangutans and their habitats. In future work, we aim to develop orangutan nest detector, contributing to wildlife conservation research.

Development of silica gel from Lapindo volcanic mud as fluorescent fingerprint powder based on methyl orange

Fingerprint powder remains one of the most effective techniques for identifying individuals from their latent fingerprints. Visualizing latent fingerprints requires powder with high color contrast and strong adhesive to be easily applied on various substrates. The utilization of silica gel extracted from local materials of Lapindo volcanic mud can be applied for fluorescent fingerprint powder based on methyl orange. The powder was synthesized by the sol-gel method, followed by the impregnation of methyl orange as a dye with varying loads. The powders exhibit an amorphous structure and nanoparticle size with an average particle diameter of 80.93 nm by spherical morphology interconnected to form agglomerations. The powder contains silanol, siloxane, azo, and carboxylate functional groups derived from its precursors. The dusting method proves the performance of fluorescent fingerprint powder on porous and non-porous substrates hereafter observed under white light and UV light. The powder containing 0.05 gs of methyl orange per gram of silica gel is the most effective in revealing fingerprint patterns on non-porous surfaces. It has mesoporous properties with a specific surface area of 7.95 m2g−1 and a pore diameter of 23.14 nm. SiMO retained its full capability after two years of storage, indicating it is a great choice for forensic investigations.

Multiple Stimuli-Responsive Color-Changing Polymer Materials for Reversible Writing and Anti-Counterfeiting.

Polymer materials with multiple stimuli-responsive properties have demonstrated many potential and practical applications. By covalently introducing spiropyran (SP1) and spirothiopyran (STP) into the polyurethane backbone, photochromic, mechanochromic, and thermally discolored polymer materials have been prepared. In this work, we report for the first time that white light (violet, blue, and green light) above a certain intensity can activate STP to green color. Based on the above discovery, the polyurethane with SP1 and STP can exhibit reversible three-color changes (brown, green, and purple) in response to four stimuli: ultraviolet irradiation, white light irradiation, mechanical stress, and heat. The color-changing polymer materials have high color contrast and excellent reversibility, and can be used for reversible writing, anticounterfeiting and information encryption, etc.

Determining the efficacy of visual inspections at detecting non-biosecurity-compliant goods.

Examination of imported commodities by trained inspectors searching for pest organisms is a common practice that phytosanitary regulatory agencies use to mitigate biosecurity risks along trade pathways. To investigate the effects of target size and color on the efficacy of these visual assessments, we affixed square decals to polystyrene models of mandarins. Sample units of 100 model fruit containing up to 10 marked models were examined by inspectors. Six sizes in six shades of brown were tested across two prevalence levels. The experiment consisted of five inspection rounds where 11 inspectors examined 77 sample units within an allocated time. The probability that decals were detected increased with mark size and color contrast. Smaller, low-contrast marks were mainly missed. The prevalence rate did not affect the detectability. Through the experiment, the false-positive rate dropped from 6% to 3%, whereas false-negative rates were constant throughout. Large, dark targets were readily found with a mean recall of >90%, whereas small, pale marks had a mean recall of 9%. Increased experience made inspectors more competent at recognizing decals, reducing the false positive rate. However, constant false-negative rates indicate that experience did not prevent inspectors from overlooking targets they could not perceive.

A fuzzy control algorithm based on artificial intelligence for the fusion of traditional Chinese painting and AI painting

Recently, artificial intelligence (AI)-generated resources have gained popularity because of their high effectiveness and reliability in terms of output and capacity to be customized and broadened, especially in image generation. Traditional Chinese paintings (TCPs) are incomplete because their color contrast is insufficient, and object reality is minimal. However, combining AI painting (AIP) with TCP remains inadequate and uncertain because of image features such as patterns, styles, and color. Hence, an algorithm named variational fusion-based fuzzy accelerated painting (VF2AP) has been proposed to resolve this challenge. Initially, the collected TCP data source is applied for preprocessing to convert it into a grayscale image. Then, the feature extraction process is performed via fuzzy-based local binary pattern (FLBP) and brushstroke patterns to enhance the fusion of intelligent fuzzy logic to optimize the local patterns of textures in a noisy image. Second, the extracted features are used as inputs to the variational autoencoder (VAE), which is used to avoid latent space irregularities in the image and the reconstructed image by maintaining minimum reconstruction loss. Third, fuzzy inference rules are applied to avoid variation in the fusion process of the reconstructed and original images. Fourth, the feedback mechanism is designed with evaluation metrics such as area under the curve-receiver operating characteristic (AUC-ROC) analysis, mean square error (MSE), structural similarity index (SSIM), and Kullback‒Leibler (KL) divergence to enhance the viewer's understanding of fused painting images.

Automated Cobb Angle Measurements for Scoliosis Diagnosis and Assessment: AI Applications and Accuracy Enhancement Through Image Processing Techniques.

Introduction Scoliosis is characterized by an abnormal curvature of the spine in the coronal plane. Idiopathic scoliosis is the most prevalent type, though specific causes are sometimes identifiable. Genetic factors significantly influence adolescent idiopathic scoliosis (AIS), which is diagnosed through clinical and radiographic evaluations, primarily using the Cobb angle to measure curvature severity. The classification of scoliosis severity ranges from mild scoliosis, where sometimes the absence of pain is encountered, to moderate and severe, which is usually associated with lancinating pain. Early onset and high progression rates in idiopathic scoliosis are indicative of poorer prognoses. Methods The study analyzed 197 radiographic images from a private clinic database between December 2023 and April 2024. Inclusion criteria focused on anteroposterior images of the thorax and abdomen, excluding unclear and non-spinal images. Manual Cobb angle measurements were performed using RadiAnt DICOM Viewer 2020.2, followed by automated measurements using the Cobb Angle Calculator software. Discrepancies led to further image processing with enhanced color contrast for improved visualization. Data were analyzed using GraphPad InStat to assess error margins between manual and automated measurements. Results Initial results indicated discrepancies between manual and automated Cobb angle measurements. Enhanced image processing improved accuracy, demonstrating the efficacy of both manual and automated techniques in evaluating spinal deformities. Statistical analysis revealed significant error margins, prompting a refined approach for minimizing measurement errors. Discussion The study highlights the importance of accurate Cobb angle measurement in diagnosing and classifying scoliosis. Manual measurements, while reliable, are time-consuming and prone to human error. Automated methods, particularly those enhanced by machine learning algorithms, offer promising accuracy and efficiency. The integration of image processing techniques further enhances the reliability of scoliosis evaluation. Conclusion Accurate assessment of scoliosis through Cobb angle measurement is crucial for effective diagnosis and treatment planning. The study demonstrates that combining manual techniques with advanced automated methods and image processing significantly improves measurement accuracy. Such an approach is intended to support better clinical outcomes. Future research should focus on refining these technologies for broader clinical applications.