Color Calibration Research Articles

Standardizing HER2 immunohistochemistry assessment: calibration of color and intensity variation in whole slide imaging caused by staining and scanning

In the evaluation of human epidermal growth factor receptor 2 (HER2) immunohistochemistry (IHC) — one of the standard biomarkers for breast cancer— visual assessment is laborious and subjective. Image analysis using whole slide image (WSI) could produce more consistent results; however, color variability in WSIs due to the choice of stain and scanning processes may impact image analysis. We therefore developed a calibration protocol to diminish the staining and scanning variations of WSI using two calibrator slides. The IHC calibrator slide (IHC-CS) contains peptide-coated microbeads with different concentrations. The color distribution obtained from the WSI of stained IHC-CS reflects the staining process and scanner characteristics. A color chart slide (CCS) is also useful for calibrating the color variation due to the scanner. The results of the automated HER2 assessment were compared to confirm the effectiveness of two calibration slides. The IHC-CS and HER2 breast cancer cases were stained on different days. All stained slides and CCS were digitized by two different WSI scanners. Results revealed 100% concordance between automated evaluation and the pathologist’s assessment with both the scanner and staining calibration. The proposed method may enable consistent evaluation of HER2.

Development of a Cloud-Based Image Processing Health Checkup System for Multi-Item Urine Analysis.

With the busy pace of modern life, an increasing number of people are afflicted by lifestyle diseases. Going directly to the hospital for medical checks is not only time-consuming but also costly. Fortunately, the emergence of rapid tests has alleviated this burden. Accurately interpreting test results is extremely important; misinterpreting the results of rapid tests could lead to delayed medical treatment. Given that URS-10 serve as a rapid test capable of detecting 10 distinct parameters in urine samples, the results of assessing these parameters can offer insights into the subject's physiological condition. These parameters encompass aspects such as metabolism, renal function, diabetes, urinary tract disorders, hemolytic diseases, and acid-base balance, among others. Although the operational procedure is straightforward, the variegated color changes exhibited in the outcomes of individual parameters render it challenging for lay users to deduce causal factors solely from color variations. Moreover, potential misinterpretations could arise due to visual discrepancies. In this study, we successfully developed a cloud-based health checkup system that can be used in an indoor environment. The system is used by placing a URS-10 test strip on a colorimetric board developed for this study, then using a smartphone application to take images which are uploaded to a server for cloud computing. Finally, the interpretation results are stored in the cloud and sent back to the smartphone to be checked by the user. Furthermore, to confirm whether the color calibration technology can eliminate color differences between different cameras, and also whether the colorimetric board and the urine test strips can perform color comparisons correctly in different light intensity environments, indoor environments that could simulate a specific light intensity were established for testing purposes. When comparing the experimental results to real test strips, only two groups failed to reach an identification success rate of 100%, and in both of these cases the success rate reached 95%. The experimental results confirmed that the system developed in this study was able to eliminate color differences between camera devices and could be used without special technical requirements or training.

Compact imaging system and deep learning based segmentation for objective longissimus muscle area in Korean beef carcass

With growing consumer interest in meat quality, the need for accurate quality assessment becomes increasingly important. One crucial factor of Korean beef quality is the longissimus muscle area, which is closely associated with both quality and yield grade. Currently, the measurement is visually assessed, introducing subjectivity and placing a substantial burden on inspectors in terms of labor. To address these challenges, we have developed a compact image acquisition system designed to acquire accurate grading assessment images of beef carcasses. Several preprocessing steps after image acquisition were conducted, including radial distortion correction and color calibration. We have employed conventional image-processing techniques and four deep-learning models to segment the longissimus muscle area using the calibrated images. Among the segmentation models, DeepLab model based on ResNet50 achieved the highest accuracy. It demonstrated a Global Accuracy, Weighted IoU, and Mean BF Score of approximately 99.26%, 98.54%, and 95.70%, respectively. The results of our study are expected to contribute to the development of objective criteria for loin area assessment. By enabling precise and consistent determination of beef carcass quality, our research has the potential to reduce labor requirements for inspectors and provide a standardized approach to assessing loin area.

Color difference evaluations on metameric color stimuli by observers of three age groups.

Color matching functions (CMFs), which are used to derive tristimulus values and chromaticities, play a very important role in color characterization, calibration, and specifications. Great efforts have been made to investigate how CMFs can characterize the color matches and mismatches between stimuli with different spectral compositions under different sizes of field of view (FOV). Few study specifically investigated how to better characterize the CMFs for different observer ages. In this study, we carefully designed a series of color stimuli using different CMFs based on our two past studies, and asked 51 young, middle-aged, and senior observers to evaluate the color differences. The three sets of CIE 2006 CMFs (i.e., 10°, 4°, and 2°) with an age of 20-, 40-, and 70-year were found to characterize the perceived color differences for the young, middle-aged, and senior observers. In addition, it was found that the characterization of a group of observers can also be performed using these three sets of CMFs based on the distributions of the observers, which had a better correlation to the perceived color differences than the individual colorimetric model.

Color Calibration in Virtual Reality Using Different Head Mounted Displays

Color Calibration in Virtual Reality Using Different Head Mounted Displays

Color Calibration based on Mosaic Stitching of a Color Target as an Alternative to a Single-shot Approach

Color Calibration based on Mosaic Stitching of a Color Target as an Alternative to a Single-shot Approach

Vision-Based White Radish Phenotypic Trait Measurement with Smartphone Imagery

White radish is a nutritious and delectable vegetable that is enjoyed globally. Conventional techniques for monitoring radish growth are arduous and time-consuming, encouraging the development of novel methods for quicker measurements and greater sampling density. This research introduces a mathematical model working on high-resolution images to measure radish’s biophysical properties automatically. A color calibration was performed on the dataset using a color checker panel to minimize the impact of varying light conditions on the RGB images. Subsequently, a Mask-RCNN model was trained to effectively segment different components of the radishes. The observations of the segmented results included leaf length, leaf width, root width, root length, leaf length to width, root length to width, root shoulder color, and root peel color. The automated real-life measurements of these observations were then conducted and compared with actual results. The validation results, based on a set of white radish samples, demonstrated the models’ effectiveness in utilizing images for quantifying phenotypic traits. The average accuracy of the automated method was confirmed to be 96.2% when compared to the manual method.

Calibration of head mounted displays for vision research with virtual reality.

Immersion in virtual environments is an important analog for scientists. Situations that cannot be safely organized in the real world are being simulated virtually to observe, evaluate, and train aspects of human behavior for psychology, therapy, and assessment. However, creating an immersive environment using traditional graphics practices may create conflict with a researcher's goal of evaluating user response to well-defined visual stimuli. Standard computer monitors may display color-accurate stimuli, but it is generally viewed from a seating position, where the participant can see real-world visual context. In this article, we propose a novel means to allow vision scientists to exert finer control over the participants visual stimuli and context. We propose and verify a device-agnostic approach to color calibration by analyzing display properties such as luminance, spectral distribution, and chromaticity. We evaluated five different head-mounted displays from different manufacturers and showed how our approach produces conforming visual outputs.

Digitization of natural history collections: A guideline and nationwide capacity building workshop in Malaysia.

Natural history museum collections are the most important sources of information on the present and past biodiversity of our planet. Most of the information is primarily stored in analogue form, and digitization of the collections can provide further open access to the images and specimen data to address the many global challenges. However, many museums do not digitize their collections because of constraints on budgets, human resources, and technologies. To encourage the digitization process, we present a guideline that offers low-cost and technical knowledge solutions yet balances the quality of the work and outcomes. The guideline describes three phases of digitization, namely preproduction, production, and postproduction. The preproduction phase includes human resource planning and selecting the highest priority collections for digitization. In the preproduction phase, a worksheet is provided for the digitizer to document the metadata, as well as a list of equipment needed to set up a digitizer station to image the specimens and associated labels. In the production phase, we place special emphasis on the light and color calibrations, as well as the guidelines for ISO/shutter speed/aperture to ensure a satisfactory quality of the digitized output. Once the specimen and labels have been imaged in the production phase, we demonstrate an end-to-end pipeline that uses optical character recognition (OCR) to transfer the physical text on the labels into a digital form and document it in a worksheet cell. A nationwide capacity workshop is then conducted to impart the guideline, and pre- and postcourse surveys were conducted to assess the confidence and skills acquired by the participants. This paper also discusses the challenges and future work that need to be taken forward for proper digital biodiversity data management.

Method and analysis of color changes of facial skin after applying skin makeup

This study investigated facial skin color differences before and after makeup. Toward this goal, a photo gauge, devised with a pair of color checkers as a reference, collected face images. In addition, color calibration and a deep-learning method extracted the color values of representative areas of facial skin. The photo gauge photographed 516 Chinese females before and after applying makeup. Then, the collected images were calibrated by referencing skin color patches, and the lower cheek regions’ pixel colors were extracted using open-source computer vision libraries. Following the visible color spectrum of humans, the color values were computed in L*, a*, and b* of CIE1976L*a*b*. The results showed that the facial colors of the Chinese females changed to become brighter, less reddish, and less yellowish after applying the makeup, resulting in a paler skin tone. During the experiment, subjects were given five varieties of liquid foundation to choose one sample that best fits their skin. However, we failed to find any noticeable relationship between the individual’s facial skin color characteristics and the liquid foundation selected. In addition, 55 subjects were identified according to their makeup use frequency and skill, but their color changes did not differ from the other subjects. This study provided quantitative evidence of makeup trends in the Shanghai region in China, and the method proposes a novel approach toward remote skin color research.

Iterative Development, Validation, and Certification of a Smartphone System to Assess Neonatal Jaundice: Development and Usability Study.

Medical device development is an area facing multiple challenges, resulting in a high number of products not reaching the clinical setting. Neonatal hyperbilirubinemia, manifesting as neonatal jaundice (NNJ), is an important cause of newborn morbidity and mortality. It is important to identify infants with neonatal hyperbilirubinemia at an early stage, but currently there is a lack of tools that are both accurate and affordable. This study aimed to develop a novel system to assess the presence of NNJ. The device should provide accurate results, be approved as a medical device, be easy to use, and be produced at a price that is affordable even in low-resource settings. We used an iterative approach to develop a smartphone-based system to detect the presence of NNJ. We performed technical development, followed by clinical and usability testing in parallel, after which we initiated the regulatory processes for certification. We updated the system in each iteration, and the final version underwent a clinical validation study on healthy term newborns aged 1 to 15 days before all documentation was submitted for conformity assessment to obtain Conformité Européenne (CE) certification. We developed a system that incorporates a smartphone app, a color calibration card, and a server. Three iterations of the smartphone-based system were developed; the final version was approved as a medical device after complying with Medical Device Regulation guidelines. A total of 201 infants were included in the validation study. Bilirubin values using the system highly correlated with total serum or plasma bilirubin levels (r=0.84). The system had a high sensitivity (94%) to detect severe jaundice, defined as total serum or plasma bilirubin >250 µmol/L, and maintained a high specificity (71%). Our smartphone-based system has a high potential as a tool for identifying NNJ. An iterative approach to product development, conducted by working on different tasks in parallel, resulted in a functional and successful product. By adhering to the requirements for regulatory approval from the beginning of the project, we were able to develop a market-ready mobile health solution.

A Wavelength-Dependent Visible Light Communication Channel Model for Underground Environments and Its Performance Using a Color-Shift Keying Modulation Scheme

Reliable wireless communications are crucial for ensuring workers’ safety in underground tunnels and mines. Visible light communications (VLC) have been proposed as auxiliary systems for short-range wireless communications in underground environments due to their seamless availability, immunity to electromagnetic interference, and illumination capabilities. Although multiple VLC channel models have been proposed for underground mines (UM) so far, none of these models have considered the wavelength dependence of the underground mining VLC channel (UM-VLC). In this paper, we propose a single-input, single-output (SISO), wavelength-dependent UM-VLC channel model considering the wavelength dependence of the light source, reflections, light scattering, and the attenuation due to dust and the photodetector. Since wavelength dependence allows us to model VLC systems more accurately with color-based modulation, such as color-shift keying (CSK), we also propose a wavelength-dependent CSK-based UM-VLC channel model. We define a simulation scenario in an underground mine roadway and calculate the received power, channel impulse response (CIR), signal-to-noise ratio (SNR), signal-to-interference ratio (SIR), root mean square (RMS) delay, and bit error rate (BER). For comparison, we also calculate these parameters for a monochromatic state-of-the-art UM-VLC channel and use it as a reference channel. We find that the inclusion of wavelength-dependency in CSK-based UM-VLC systems plays a significant role in their performance, introducing color distortion that the color calibration algorithm defined in the IEEE 802.15.7 VLC standard finds harder to revert than the linear color distortion induced by monochromatic CSK channels.

AI-Assisted Assessment of Wound Tissue with Automatic Color and Measurement Calibration on Images Taken with a Smartphone.

Wound assessment is essential for evaluating wound healing. One cornerstone of wound care practice is the use of clinical guidelines that mandate regular documentation, including wound size and wound tissue composition, to determine the rate of wound healing. The traditional method requires wound care professionals to manually measure the wound area and tissue composition, which is time-consuming, costly, and difficult to reproduce. In this work, we propose an approach for automatic wound assessment that incorporates automatic color and measurement calibration and artificial intelligence algorithms. Our approach enables the comparison of images taken at different times, even if they were taken under different lighting conditions, distances, lenses, and camera sensors. We designed a calibration chart and developed automatic algorithms for color and measurement calibration. The wound area and wound composition on the images were annotated by three physicians with more than ten years of experience. Deep learning models were then developed to mimic what the physicians did on the images. We examined two network variants, U-Net with EfficientNet and U-Net with MobileNetV2, on wound images with a size of 1024 × 1024 pixels. Our best-performing algorithm achieved a mean intersection over union (IoU) of 0.6964, 0.3957, 0.6421, and 0.1552 for segmenting a wound area, epithelialization area, granulation tissue, and necrotic tissue, respectively. Our approach was able to accurately segment the wound area and granulation tissue but was inconsistent with respect to the epithelialization area and necrotic tissue. The calibration chart, which helps calibrate colors and scales, improved the performance of the algorithm. The approach could provide a thorough assessment of the wound, which could help clinicians tailor treatment to the patient's condition.

Improving the reliability of smartphone-based urine colorimetry using a colour card calibration method.

Urine colorimetry using a digital image-based colorimetry is potentially an accessible hydration assessment method. This study evaluated the agreement between urine colorimetry values measured with different smartphone brands under various lighting conditions in patients with dengue fever. The urine samples were photographed in a customized photo box, under five simulated lighting conditions, using five smartphones. These images were analyzed using Adobe Photoshop to obtain urine Red, Green and Blue (RGB) values with and without colour correction. A commercially available colour calibration card was used for colour correction. Using intraclass correlation coefficient (ICC), inter-phone and intra-phone agreements of urine RGB values were analyzed. Without colour correction, the various smartphones produced the highest agreement for Blue and Green values under the 'daylight' lighting condition. With colour correction, ICC values showed 'exceptional' inter-phone and intra-phone agreement for the Blue and Green values (ICC > 0.9). Red values showed 'poor' (ICC < 0.5) agreement with and without colour correction in all lighting conditions. Out of the five phones compared in this study, Phone 4 produced the lowest intra-phone agreement. Colour calibration using photo colour cards improved the reliability of smartphone-based urine colorimetry, making this a promising point-of-care hydration assessment tool using the ubiquitous smartphone.

The Calibration of Dispersion Staining Colors

Dispersion staining (DS) is an effective and versatile technique for measuring the refractive index (RI) of non-opaque materials by polarized light microscopy (PLM) and has been widely applied in the analysis of asbestos minerals. DS converts the RI difference between an object and its surrounding liquid medium with known RI into an observable color, i.e., the DS color, in the visible spectrum, resulting from the corresponding matching wavelength λm between the RI of the object and its surrounding liquid. Based on the relationship between DS color and λm, λm can be quantitatively evaluated from the observed DS color. Once λm is known, the RI difference between the object and liquid can be calculated. From the liquid’s RI value, the RI value of the object is then measured. The accuracy of RI measurement is directly and primarily dependent on the accuracy of the DS color estimation. Therefore, it’s paramount to obtain an accurate estimation of DS color. In order to improve the accuracy of DS color estimation, it must be carefully calibrated against the specific polarized light microscope used and the specific eyes of the analyst performing the measurement. This paper presents a practical, step-by-step procedure for the calibration of DS color with necessary RI-λm conversion tables at different working temperatures.

Whiteness measurement of Agaricus bisporus based on image processing and color calibration model

Whiteness measurement of Agaricus bisporus based on image processing and color calibration model

An Optical POCT Device for Colorimetric Detection of Urine Test Strips Based on Raspberry Pi Imaging

Urine examinations are widely applied in hospitals using urine test strip analyzers or other sophisticated professional instruments. However, such methods are inconvenient health monitoring of patients at home. Herein, we construct an optical device for point-of-care testing (POCT) for urine analysis at home or on the spot. A black box and color calibration curve are established to eliminate the influence of ambient light with an independent internal lighting system included in the device. A Raspberry Pi with a CSI camera is programmed to automatically collect the strip images and identify the HSV values of the image with an image processing algorithm. During this process, these corrected colors are converted to concentration values by preloaded standard curves. Under optimal conditions, the proposed POCT device can quantitatively and automatically detect glucose within 1 min, with linear detection ranging from 2 mM to 60 mM and a detection limit of 1.16 mM. In addition, the device demonstrates satisfactory accuracy and quantitative analysis of ketone bodies, glucose, protein, occult blood, pH, and leukocytes in human urine samples with high-resolution concentrations, achieving results similar to those obtained with hospital instruments. The proposed device is portable and user-friendly, providing convenient colorimetric analysis for urine. Furthermore, the proposed device also has considerable potential for the development of in vitro diagnosis methods through combination with other test strips.

Framework to select refining parameters in Total fringe order photoelasticity (TFP)

What makes Total fringe order photoelasticity (TFP) the ideal digital photoelastic technique for industrial applications is the sufficiency of a single colour isochromatic image for fringe order evaluation and the convenience of capturing this image using easily accessible, relatively cheap hardware. In TFP, the colour information in the application image is matched with an experimental colour calibration table. A simple least squares colour matching is insufficient for this due to errors caused by the repetition of colour in the isochromatics. This is rectified through a process called fringe order refinement. Among the existing fringe order refining methods, the combination of – flexible seeding, window search method, and FRSTFP scanning – has proved to be the best choice for solving a variety of problems for the complete model domain. The successful application of this combination requires the right choice of parameter values for its constituent methods. A systematic parametric study of these refining parameters is a lacuna in the literature, which is addressed in this work, by selecting a variety of problems. The study has revealed the interconnection between the refining parameters, which has helped to formulate a set of recommendations for selecting the same. It is found that some of the existing understandings on refining parameters require a relook. The difficulty in refining fringe fields having multiple fringe gradient reversals with a single set of parameters is illustrated, and how this can be overcome by local refinement is brought out. Additionally, a methodology to track the source of refining error is proposed.

Pixel-wise structured light calibration method with a color calibration target.

We propose to use a calibration target with a narrow spectral color range for the background (e.g., from blue) and broader spectral color range for the feature points (e.g., blue + red circles), and fringe patterns matching the background color for accurate phase extraction. Since the captured fringe patterns are not affected by the high contrast of the calibration target, phase information can be accurately extracted without edging artifacts. Those feature points can be clearly "seen" by the camera if the ambient light matches the feature color or without the background color. We extract each calibration pose for three-dimensional coordinate determination for each pixel, and then establish pixel-wise relationship between each coordinate and phase. Comparing with our previously published method, this method significantly fundamentally simplifies and improves the algorithm by eliminating the computational framework estimate smooth phase near high-contrast feature edges. Experimental results demonstrated the success of our proposed calibration method.

Simple Color Calibration Method by Projection onto Retroreflective Materials.

Retroreflective materials have the property of directional reflection, reflecting light strongly in the direction of the light source, and have been used for road traffic signs. In recent years, retroreflective materials have been used in entertainment and industrial technologies, in combination with projection mapping technology. In general, color calibration is important when projectors are used to control reflected colors. In this study, we investigated a simple color calibration method for retroreflective materials with a 3D shape under the condition that they are observed in the same direction as the light source. Three types of retroreflective materials with different reflective properties were used. First, to measure the reflective properties of each reflective material, the reflective material was fixed to a flat plate and rotated, while the reflected light was measured in the same direction as the light source. It was then confirmed that the reflected light intensity varied smoothly with angular change, and appropriate measurement angles were investigated based on the AIC criterion, aiming to interpolate the reflectance characteristics from a small number of measurement angles. Color calibration was performed based on the reflectance characteristics obtained from the derived measurement angles, and the experiments showed that good color calibration was possible with fewer measurements.