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34 results for “Colour images”
Does colour impact responses to images in geckos?
<p>Animals are exposed to different visual stimuli that influence how they perceive and interact with their environment. Visual information such as shape and colour can help the animal detect, discriminate and make appropriate behavioural decisions for mate selection, communication, camouflage, and foraging. In all major vertebrate groups, it has been shown that certain species can discriminate and prefer certain colours and that colours may increase the response to a stimulus. However, since colour is often studied together with other potentially confounding factors, it is still unclear what role colour plays in the perception of and attention to biologically relevant and familiar stimuli versus novel stimuli. In this study, we test whether colour influences the response that an animal has to an object, and if this influence – if any – changes depending on the object shown to the animal. We therefore assessed the response of three gecko species Correlophus ciliatus, Eublepharis macularius, and Phelsuma laticauda to familiar and novel objects presented as colour or grayscale images. Our results indicate that colour did not change the animal's response to any of the objects. Specifically, we found that while all species responded more often to the novel than to the familiar images, colour did not influence the response. We also found that the duration of interaction with images was significantly longer for the diurnal species, P. laticauda, than for the two nocturnal species, but this was again independent from colouration. Finally, no differences among sexes were observed within or across species. Our results indicate that geckos discriminate between 2D images of different content independent of colouration, suggesting that colouration may not increase detectability or intensity of the response. These results are essential for uncovering which visual stimuli produce a response in animals</p>
OPTIMA - RGB colour images and multispectral images (including LabelImg annotations)
<p>The images and annotations (LabelImg) in this folder are acquired during the H2020 OPTIMA project. The images were acquired in orchards, vineyards and fields in three European countries (France, Italy, Spain). The images represent three diseases in three crops: apple scab in apple, alternaria in carrot, downy mildew in grape. The txt files contain the bounding box locations for the diseases (bounding box detection for YOLOv5 object detection). </p> <p>The folder contains three subfolders:</p> <ol> <li>apple_applescab <ol> <li>ms: multispectral images acquired on 10-05-2022 in Spain with the Silios multispectral camera</li> <li>rgb: rgb colour images acquired on 27-05-2021 and 10-06-2021 in Spain with the NEON-202B-JT2-X smart-camera</li> </ol> </li> <li>carrot_alternaria <ol> <li>ms: multispectral images acquired on 23-09-2021 and 24-09-2021 in France with the Silios multispectral camera</li> <li>rgb: rgb colour images acquired on 02-09-2021, 24-09-2021, and 04-11-2021 in France with the NEON-201B-JT2-X smart-camera</li> </ol> </li> <li>grape_downymildew <ol> <li>ms: multispectral images acquired on 06-06-2019 in Italy with the IMEC multispectral camera</li> <li>rgb: rgb colour images acquired on 23-07-2021 in Italy with the NEON-201B-JT2-X smart-camera</li> </ol> </li> </ol>
Computer-assisted Diagnosis System Based on Linked Colour Imaging
ClinicalTrials.gov study NCT03359343. IPD Sharing: UNDECIDED. Countries: 1. Publications: 3.
Does colour impact responses to images in geckos?
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Data from: The evolution of colour polymorphism in British winter‐active Lepidoptera in response to search image use by avian predators
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Data from: Image Calibration and Analysis Toolbox – a free software suite for measuring reflectance, colour, and pattern objectively and to animal vision
1. Quantitative measurements of colour, pattern, and morphology are vital to a growing range of disciplines. Digital cameras are readily available and already widely used for making these measurements, having numerous advantages over other techniques, such as spectrometry. However, off-the-shelf consumer cameras are designed to produce images for human viewing, meaning that their uncalibrated photographs cannot be used for making reliable, quantitative measurements. Many studies still fail to appreciate this, and of those scientists who are aware of such issues, many are hindered by a lack usable tools for making objective measurements from photographs. 2. We have developed an image processing toolbox that generates images that are linear with respect to radiance from the RAW files of numerous camera brands, and can combine image channels from multispectral cameras, including additional ultraviolet photographs. Images are then normalised using one or more grey standards to control for lighting conditions. This enables objective measures of reflectance and colour using a wide range of consumer cameras. Furthermore, if the camera's spectral sensitivities are known, the software can convert images to correspond to the visual system (cone-catch values) of a wide range of animals, enabling human and non-human visual systems to be modelled. The toolbox also provides image analysis tools that can extract luminance (lightness), colour, and pattern information. Furthermore, all processing is performed on 32-bit floating point images rather than commonly used 8-bit images. This increases precision and reduces the likelihood of data loss through rounding error or saturation of pixels, while also facilitating the measurement of objects with shiny or fluorescent properties. 3. All cameras tested using this software were found to demonstrate a linear response within each image and across a range of exposure times. Cone-catch mapping functions were highly robust, converting images to several animal visual systems and yielding data that agreed closely with spectrometer-based estimates. 4. Our imaging toolbox is freely available as an addition to the open source ImageJ software. We believe that it will considerably enhance the appropriate use of digital cameras across multiple areas of biology, in particular researchers aiming to quantify animal and plant visual signals.
Data from: An RGB colour image steganography scheme using overlapping block-based pixel-value differencing
This paper presents a steganographic scheme based on the RGB colour cover image. The secret message bits are embedded into each colour pixel sequentially by the pixel-value differencing (PVD) technique. PVD basically works on two consecutive non-overlapping components; as a result, the straightforward conventional PVD technique is not applicable to embed the secret message bits into a colour pixel, since a colour pixel consists of three colour components, i.e. red, green and blue. Hence, in the proposed scheme, initially the three colour components are represented into two overlapping blocks like the combination of red and green colour components, while another one is the combination of green and blue colour components, respectively. Later, the PVD technique is employed on each block independently to embed the secret data. The two overlapping blocks are readjusted to attain the modified three colour components. The notion of overlapping blocks has improved the embedding capacity of the cover image. The scheme has been tested on a set of colour images and satisfactory results have been achieved in terms of embedding capacity and upholding the acceptable visual quality of the stego-image.
Texture and Colour Enhancement Imaging in Improving Detection and Miss Rate of Premalignant Lesions
ClinicalTrials.gov study NCT06515977. IPD Sharing: Not stated. Countries: 0. Publications: 3.
Data from: An RGB colour image steganography scheme using overlapping block-based pixel-value differencing
Open the record for dataset details and reuse information.
Data from: Image Calibration and Analysis Toolbox – a free software suite for measuring reflectance, colour, and pattern objectively and to animal vision
Open the record for dataset details and reuse information.
A Randomised Paired Design Study of Texture and Colour Enhancement Imaging (TXI) Versus High-definition White Light Endoscopy
ClinicalTrials.gov study NCT07271264. IPD Sharing: NO. Countries: 0. Publications: 0.
FIGURE 4. A–D. U. hirtella s.l., E–G. U. velascoensis, H. U. tridentata, I. U. tricolor, J. U. biceps, K. U. bicolor, L. U. chapadensis, M–N. U. pantaneira, O. U. trinervia. Images C. Rivadavia, D. Rohrbacher, E–G in Unveiling Utricularia amethystina's true colours: a taxonomic revision of one of the largest species complexes (U. sect. Foliosa, Lentibulariaceae)
FIGURE 4. A–D. U. hirtella s.l., E–G. U. velascoensis, H. U. tridentata, I. U. tricolor, J. U. biceps, K. U. bicolor, L. U. chapadensis, M–N. U. pantaneira, O. U. trinervia. Images C. Rivadavia, D. Rohrbacher, E–G. by Marcos Cardoso, J., K. Gonella.
Colour Doppler Flow Imaging in Lacrimal Gland Lesions
ClinicalTrials.gov study NCT02900846. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Texture and Colour Enhancement Imaging (TXI) Versus Dye Chromoendoscopy for Dysplasia Detection in IBD Surveillance.
ClinicalTrials.gov study NCT07208214. IPD Sharing: NO. Countries: 0. Publications: 0.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.