Cindy Lorena Gómez-Heredia, Jose David Ardila-Useda, Andrés Felipe Cerón-Molina
et al.
Accurate color property measurements are critical for advancing artificial vision in real-time industrial applications. RGB imaging remains highly applicable and widely used due to its practicality, accessibility, and high spatial resolution. However, significant uncertainties in extracting chromatic information highlight the need to define when conventional digital images can reliably provide accurate color data. This work simultaneously compares six chromatic properties across 700 Pantone<sup>®</sup> TCX fabric samples, using optical data acquired simultaneously from both hyperspectral (HSI) and digital (RGB) cameras. The results indicate that the accurate interpretation of optical information from RGB (sRGB and REC2020) images is significantly influenced by lightness (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msup><mrow><mi>L</mi></mrow><mrow><mo>*</mo></mrow></msup></mrow></semantics></math></inline-formula>) values. Samples with bright and unsaturated colors (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msup><mrow><mi>L</mi></mrow><mrow><mo>*</mo></mrow></msup><mo>></mo></mrow></semantics></math></inline-formula> 50) reach ratio-to-performance-deviation (RPD) values above 2.5 for four properties (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msup><mrow><mi>L</mi></mrow><mrow><mo>*</mo></mrow></msup><mo>,</mo><mo> </mo><msup><mrow><mi>a</mi></mrow><mrow><mo>*</mo></mrow></msup><mo>,</mo><mo> </mo><msup><mrow><mi>b</mi></mrow><mrow><mo>*</mo></mrow></msup></mrow></semantics></math></inline-formula> <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>h</mi></mrow><mrow><mi>a</mi><mi>b</mi></mrow></msub></mrow></semantics></math></inline-formula>), indicating a good correlation between HSI and RGB information. Absolute color difference comparisons (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mo>∆</mo><mi>E</mi></mrow><mrow><mi>a</mi></mrow></msub></mrow></semantics></math></inline-formula>) between HSI and RGB images yield values exceeding 5.5 units for red-yellow-green samples and up to 9.0 units for blue and purple tones. In contrast, relative color differences (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mo>∆</mo><mi>E</mi></mrow><mrow><mi>r</mi></mrow></msub></mrow></semantics></math></inline-formula>) comparisons show a significant decrease, with values falling below 3.0 for all lightness values, indicating the practical equivalence of both methodologies according to the Two One-Sided Test (TOST) statistical analysis. These results confirm that RGB imagery achieves reliable color consistency when evaluated against a practical reference.
Photography, Computer applications to medicine. Medical informatics
Dr. Ateaf EL Moteay Dr. Khaled Salah El Deen researcher. May Samiir Kafafy
Photography is a universal and understandable language that spreads quickly like a virus, and its impact is powerful. Therefore, this research will focus on the most powerful iconic photojournalistic images that have changed the course of many global events.
There is no doubt that the battle that is raging today between the major industrialized countries and their domination of poor countries is a battle for control of the image in all its forms and meanings, starting with live television images via satellite, to cinema images, cartoons , and children's books
Photojournalism has had a profound impact on political decisions throughout history, influencing public opinion, exposing injustices, and even shaping the course of wars.
Here are some of the ways it has achieved this:
1. Raising awareness and influencing public opinion
2. Exposing human rights abuses and injustices
3. Holding those in power accountable
4. Shaping the narrative of wars and conflicts
Photographs can be manipulated or presented out of context, and their interpretation can be influenced by individual biases and cultural perspectives. However, at its best, photojournalism can be a powerful tool for informing the public, promoting social justice, and holding those in power accountable.
The Rise of Citizen Journalism: With the proliferation of smartphones and social media, the line between traditional photojournalism and citizen journalism has blurred. Images captured by ordinary people during protests, uprisings, or natural disasters
This article emerges from a researcher-generated longitudinal photography project conducted between 2016 and 2025 situated on the redundant site of the former Middleton Tuberculosis Hospital in North Yorkshire. The research project explored the site’s transformation through an unmanaged rewilding in the context of surrounding dairy farms within the Nidderdale ‘area of outstanding natural beauty’. The hospital site is reimagined as a bucolic ‘island’ stranded in the ideological socio-cultural notions embedded in “Nature”, the countryside, and agricultural landscape under increasing pressure to value biodiversity and nature’s restoration. Employing a reflexive lyrical critical lens informed by ‘resonance theory’, social semiotics, and expressive visual sociological practice, the article contributes to the debates surrounding landscape valorization, the contestation of the ‘countryside’ as a working, and recreational landscape. Researcher-generated photographic practice captures the duration of iterative site visits, the seasonal atmosphere and potential experience of resonance of the site, providing vivid sources for reflections, meaning-making, while proselytizing the axiom of Kress, that: ‘without frame no meaning’. The key research questions are: (1) Why is researcher-generated photography, amid AI image production, an effective epistemological method for re-presenting and understanding the significance of unmanaged landscape rewilding? (2) How do photographic re-presentations and lyrical reflexivity convey the lived resonance of being in places like the Middleton Hospital site? The text rejects illustrative photographic use in academic discourse, favoring an expressive, allusive, and lyrical interpretation of rewilding’s socio-cultural value.
During the “Glorious Thirty”, in order to develop reflection on the new “civilization of the image” and to promote the use of the photographic medium as a means of artistic expression, Albert Plécy, Raymond Grosset and Jacques Henri Lartigue founded on October 15, 1954 the Gens d’Images organization. Still active nowadays, this organization awards two annual prizes every year since 1955: the Niépce Prize, rewording the work of a French photographer, and the Nadar Prize, honoring a photographic book published in France during the year. This article traces Gens d’Images’s history, from its origins until 1985, in order to consider the influence of this association in French photography and thus highlighting certain hitherto unknown actors, events and networks that participate to the evolution of the status of photography in France during this period.
Amir-Hooshang Beheshtnejad, Hamed Ghassemi, Hossein Abdolkhalegh
et al.
Abstract Purpose: To assess the autofluorescence size and properties of pterygium and pinguecula by anterior segment autofluorescence (AS-AF) imaging and demonstrate the difference of autofluorescence size presented in AS-AF imaging compared to the extend size of the conjunctival lesion measured by anterior segment slit-lamp photography (AS-SLE). Methods: Twenty-five patients with primary pterygium and twenty-five with pinguecula were included in the study. In addition, 25 normal subjects were also enrolled as the control group. The AS-AF characteristics of pterygium and pinguecula lesions were analyzed. The size of lesions displayed in the AS-SLE photography versus the AS-AF images were also compared. AS-AF images were obtained using a Heidelberg retina angiograph which focused on the anterior segment. AS-SLE photography was acquired using a digital imaging system (BX900 HAAG-STREIT). Results: There were 44 (58.7%) male and 31 (41.3%) female patients; 19 (76%) and 20 (80%) patients had bilateral pterygium and pinguecula, respectively. All pinguecula lesions reflected hyperautofluorescence pattern in the AS-AF imaging. In 24 (96%) patients, the hyperautofluoresecence pattern was larger than the size of the clinical lesions displayed with the AS-SLE photography. Twenty-one (84%) patients with pterygium reflected a hyperautofluorescence pattern in AS-AF images; in one (4%) patient, the hyperautofluorescence pattern was larger than the clinical lesion size and four (16%) patients had no autofluorescence patterns in the AS-AF images. In the control group, in 14 (56%) subjects, a hypoautofluorescent pattern was revealed in the conjunctiva in AS-AF images. However, in 11 (44%) patients, hyperautofluorescence patterns were detected. Conclusion: AS-AF is a useful modality to monitor vascularization in conjunctival lesions. Pingueculae and pterygium show hyperautofluorescence in AS-AF imaging. The real size of the pinguecula lesions may be estimated with AS-AF characteristics, mostly presenting larger than the area size in AS-SLE photography. The autofluorescence size of the pterygium is smaller than the extent of visible pterygium in slit-lamp photography.
The article aims to highlight the particularities of photomontage as a representation of the architectural project, using photography as a supporting image. It develops an image analysis of a photomontage produced by the architects Lacaton & Vassal in the context of the competition for the construction of the FRAC Grand-Large, in Dunkirk, France, 2009. Through this examination, the following issues are addressed: the indiciality of the photographs used as a support for the photomontages, the way in which the image registers deployed by a photomontage can be presented as embodiments of an architectural project. Thus, the images become both representations and metaphors of the project, capable of serving the architects’ purpose.
Abstract The current instance segmentation method can achieve satisfactory results in common scenarios. However, under the overlap or partial occlusion between targets caused by the complex scenes, accurate segmentation of pigs remains a challenging task. To address the problem, the authors propose an instance segmentation method based on Mask Scoring region‐based convolutional neural networks (R‐CNN) (MS R‐CNN), which creates the adversarial network called MaskDis in the head branch of MS R‐CNN. The MaskDis is trained as a discriminator using a generative adversarial network, and the MS R‐CNN model is used as a generator during model training. The adversarial training enables the generator to learn context information and features at the pixel level, which effectively improves the segmentation quality under pigs’ overlapping or dense occlusions scenes. Experimental conducted on the pig object segmentation dataset show that the proposed approach achieves a precision of 92.03%, a recall of 92.18%, and an F1 score of 0.9210. Compared with the basic MS R‐CNN model, the approach achieved a 2.25% improvement in precision and 1.18% improvement in F1 score. Furthermore, the improved approach outperformed advanced instance segmentation methods such as YOLACT, Swin Transformer, YOLOv5‐seg, and SOLOv2 on COCO evaluation metrics. These experimental results demonstrate the effectiveness of the proposed approach in instance segmentation of pigs in complex scenes, providing technical support for non‐contact pig automatic management.
Jasmin Rezapour, Jasmin Rezapour, Andrew Q. Tran
et al.
PurposeTo compare optic nerve head (ONH) ovality index and rotation angle measurements based on semi-automated delineation of the clinical ONH margin derived from photographs and automated BMO configuration derived from optical coherence tomography (OCT) images in healthy and glaucomatous eyes with high-, mild- and no axial myopia.MethodsOne hundred seventy-five healthy and glaucomatous eyes of 146 study participants enrolled in the Diagnostic Innovations in Glaucoma Study (DIGS) with optic disc photographs and Spectralis OCT ONH scans acquired on the same day were stratified by level of axial myopia (non-myopic [n = 56, axial length (AL) <24 mm], mild-myopic [n = 58, AL 24–26 mm] and high-myopic [n = 32, AL >26 mm]. The clinical disc margin of each photograph was manually annotated, and semi-automated measurements were recorded of the ovality index and rotation angle based on a best-fit ellipse generated using ImageJ software. These semi-automated photograph-based measurements were compared to ovality index and rotation angle generated from custom automated BMO-based analysis using segmented OCT ONH volumes. R2 values from linear mixed effects models were used to describe the associations between semi-automated, photograph-based and automated OCT-based measurements.ResultsAverage (95% CI) axial length was 23.3 (23.0, 23.3) mm, 24.8 (24.7, 25.0) mm and 26.8 (26.6, 27.0) mm in non-myopic, mild-myopic and high-myopic eyes, respectively (ANOVA, p ≤ 0.001 for all). The R2 association (95% CI) between semi-automated photograph-based and automated OCT-based assessment of ONH OI for all eyes was [0.26 (0.16, 0.36); p < 0.001]. This association was weakest in non-myopic eyes [0.09 (0.01, 0.26); p = 0.02], followed by mild-myopic eyes [0.13 (0.02, 0.29); p = 0.004] and strongest in high-myopic eyes [0.40 (0.19, 0.60); p < 0.001]. No significant associations were found between photography- and OCT-based assessment of rotation angle with R2 values ranging from 0.00 (0.00, 0.08) in non-myopic eyes to 0.03 (0.00, 0.21) in high-myopic eyes (all associations p ≥ 0.33).ConclusionsAgreement between photograph-based and automated OCT-based ONH morphology measurements is limited, suggesting that these methods cannot be used interchangeably for characterizing myopic changes in the ONH.
Abstract Background To assess and characterize neovascularization of the optic disc (NVD) using optical coherence tomography angiography (OCTA) and different OCTA-based methods. Methods This retrospective, observational study included patients who were suspected of having early PDR with no presence of clinically apparent neovascularization (NV) bur were clinically diagnosed with proliferative diabetic retinopathy (PDR), or severe NPDR. Patients underwent standard clinical examinations and OCTA imaging using a 6 × 6 montage scan. Two trained graders identified NVD using different imaging systems (ultra-widefield-colour fundus photography (UWF-CFP), OCT, OCTA and fluorescein angiography (FA)). Moreover, morphological classification of NVD was performed. The detection and morphological classification of NVD by different OCTA-based methods (B-scan OCTA, En-face OCTA, VRI Angio and VRI Structure) were compared. Results A total of 169 eyes (126 eyes with PDR and 43 eyes with severe NPDR) of 123 participants were included in this study. The detection rate of NVD was 34.91% by UWF-CFP compared with 59.76% by OCT, 59.76% by OCTA, and 62.72% by FA. After excluding 2 cases with epiretinal membranes, the NVD diagnosis detected by OCT was used as the standard. Among 99 eyes diagnosed with NVD by OCT, B-scan OCTA detected NVD with a sensitivity of 97.98%, which was higher than that by en face OCTA (80.81%), VRI Angio (65.66%), and VRI Structure (61.62%) (all P < 0.05). According to its characteristics on OCTA, NVD was divided into four types (12 cases of type I, 6 cases of type II, 39 cases of type III, and 42 cases of type IV). For type I, B-scan OCTA exhibited a higher diagnostic sensitivity than other methods (P < 0.05). For types II and IV, there were no statistically significant differences in the sensitivity of various methods between the two groups (P > 0.05). Conclusion OCTA and different OCTA-based methods are significant to the diagnosis of NVD, and the diagnostic accuracy of different detection methods may be related to different types of NVD.
Abstract PM2.5 can bring serious harm to people's health and life because it easily causes cardiovascular disease and increases the risk of cancer. Hence, monitoring PM2.5 real‐timely becomes a key problem in environmental protection. Towards this end, this paper proposes an improved picture‐based prediction method of PM2.5 concentration using artificial neural network (ANN). Firstly, the weather image is transformed into Hue, Saturation, Value (HSV) color space to extract its saturation map, then the corresponding spatial and transform‐based entropy features of image space are extracted. Secondly, the PM2.5 concentration model is built based on the two extracted features from the weather image using Artificial Neural Network (ANN) theory. Thirdly, an ANN model is trained using the pre‐processed data. The training parameters and conditions are also explored through multiple experiments to achieve the best model accuracy. Experimental results show that the model has the best prediction effect when comparing to other state‐of‐the‐art models.