Search results for "Color model"
showing 10 items of 112 documents
A new multimodal RGB and polarimetric image dataset for road scenes analysis
2020
International audience; Road scene analysis is a fundamental task for both autonomous vehicles and ADAS systems. Nowadays, one can find autonomous vehicles that are able to properly detect objects present in the scene in good weather conditions but some improvements are left to be done when the visibility is altered. People claim that using some non conventional sensors (infra-red, Lidar, etc.) along with classical vision enhances road scene analysis but still when conditions are optimal. In this work, we present the improvements achieved using polarimetric imaging in the complex situation of adverse weather conditions. This rich modality is known for its ability to describe an object not o…
Blood vessels and feature points detection on retinal images
2009
In this paper we present a method for the automatic extraction of blood vessels from retinal images, while capturing points of intersection/overlap and endpoints of the vascular tree. The algorithm performance is evaluated through a comparison with handmade segmented images available on the STARE project database (STructured Analysis of the REtina). The algorithm is performed on the green channel of the RGB triad. The green channel can be used to represent the illumination component. The matched filter is used to enhance vessels w.r.t. the background. The separation between vessels and background is accomplished by a threshold operator based on gaussian probability density function. The len…
Unsupervised Clustering in Personal Photo Collections
2008
In this paper we propose a probabilistic approach for the automatic organization of collected pictures aiming at more effective representation in personal photo albums. Images are analyzed and described in two representation spaces, namely, faces and background. Faces are automatically detected, rectified and represented projecting the face itself in a common low dimensional eigenspace. Backgrounds are represented with low-level visual features based on RGB histogram and Gabor filter energy. Face and background information of each image in the collection is automatically organized by mean-shift clustering technique. Given the particular domain of personal photo libraries, where most of the …
Mean shift clustering for personal photo album organization
2008
In this paper we propose a probabilistic approach for the automatic organization of pictures in personal photo album. Images are analyzed in term of faces and low-level visual features of the background. The description of the background is based on RGB color histogram and on Gabor filter energy accounting for texture information. The face descriptor is obtained by projection of detected and rectified faces on a common low dimensional eigenspace. Vectors representing faces and background are clustered in an unsupervised fashion exploiting a mean shift clustering technique. We observed that, given the peculiarity of the domain of personal photo libraries where most of the pictures contain fa…
Skin Erythema Assessment by an RGB Imaging Device: a Clinical Study
2015
In this study, skin erythema assessment of 90 rosacea patients was estimated by a simple, low-cost RGB imaging device. A new erythema index assessment algorithm is proposed and clinically validated. Comparison with dermatologist’s visual assessment shows high correlation.
Prediction of banana quality indices from color features using support vector regression
2015
Banana undergoes significant quality indices and color transformations during shelf-life process, which in turn affect important chemical and physical characteristics for the organoleptic quality of banana. A computer vision system was implemented in order to evaluate color of banana in RGB, L*a*b* and HSV color spaces, and changes in color features of banana during shelf-life were employed for the quantitative prediction of quality indices. The radial basis function (RBF) was applied as the kernel function of support vector regression (SVR) and the color features, in different color spaces, were selected as the inputs of the model, being determined total soluble solids, pH, titratable acid…
Kinetics of Surface Chemical Reactions from a Digital Video
2020
In the last few years, the color analysis of the studied surface has been regarded as a nonexpensive way to obtain not only the spectrochemical data but also the spatiotemporal information of the entire surface. Mean color intensities and standard deviation calculated from the red, green, and blue color histograms of digital images of surfaces have been considered particularly useful for the chemical understanding of surface kinetics. The shape of curves, the maximum of peaks, or the half-peak widths depend on the kinetic constants and on the kinetic order of the surface chemical process. Some strategies used for obtaining the kinetics from RGB color intensities and their standard deviation…
Estimation of Leaf Area in Bell Pepper Plant using Image Processing techniques and Artificial Neural Networks
2021
Measurement and estimation of physical properties of plant leaves have always been considered as important requirements for monitoring and optimizing of plant growth. This study aimed at utilization of image processing and artificial intelligence techniques for non-invasive and non-destructive estimation of bell pepper leaves properties in the first month of growth. Physical properties of bell pepper plant leaves were extracted from RGB images. The algorithm makes use of gradient magnitude and watershed image. Leaf area as the most important index of growth was estimated as a function of other physical parameters including leaf length, width, perimeter etc. Using stereo imaging, the leaf di…
Maximum likelihood difference scaling of image quality in compression-degraded images.
2007
International audience; Lossy image compression techniques allow arbitrarily high compression rates but at the price of poor image quality. We applied maximum likelihood difference scaling to evaluate image quality of nine images, each compressed via vector quantization to ten different levels, within two different color spaces, RGB and CIE 1976 L(*)a(*)b(*). In L(*)a(*)b(*) space, images could be compressed on average by 32% more than in RGB space, with little additional loss in quality. Further compression led to marked perceptual changes. Our approach permits a rapid, direct measurement of the consequences of image compression for human observers.
High-end colorimetric display characterization using an adaptive training set
2011
A new, accurate, and technology-independent display color-characterization model is introduced. It is based on polyharmonic spline interpolation and on an optimized adaptive training data set. The establishment of this model is fully automatic and requires only a few minutes, making it efficient in a practical situation. The experimental results are very good for both the forward and inverse models. Typically, the proposed model yields an average model prediction error of about 1 ∆Eab* unit or below for several displays. The maximum error is shown to be low as well. freedom given to the model considering the choice of a tar- get color space and of the kernel and smoothing factor for the int…