Search results for "Color model"
showing 10 items of 112 documents
HIGH QUALITY TEXTURE MAPPING PROCESS AIMED AT THE OPTIMIZATION OF 3D STRUCTURED LIGHT MODELS
2019
Abstract. This article presents the evaluation of a pipeline to develop a high-quality texture mapping implementation which makes it possible to carry out a semantic high-quality 3D textured model. Due to geometric errors such as camera parameters or limited image resolution or varying environmental parameters, the calculation of a surface texture from 2D images could present several color errors. And, sometimes, it needs adjustments to the RGB or lightness information on a defined part of the texture. The texture mapping procedure is composed of mesh parameterization, mesh partitioning, mesh segmentation unwraps, UV map and projection of island, UV layout optimization, mesh packing and mes…
UAS BASED TREE SPECIES IDENTIFICATION USING THE NOVEL FPI BASED HYPERSPECTRAL CAMERAS IN VISIBLE, NIR AND SWIR SPECTRAL RANGES
2016
Abstract. Unmanned airborne systems (UAS) based remote sensing offers flexible tool for environmental monitoring. Novel lightweight Fabry-Perot interferometer (FPI) based, frame format, hyperspectral imaging in the spectral range from 400 to 1600 nm was used for identifying different species of trees in a forest area. To the best of the authors’ knowledge, this was the first research where stereoscopic, hyperspectral VIS, NIR, SWIR data is collected for tree species identification using UAS. The first results of the analysis based on fusion of two FPI-based hyperspectral imagers and RGB camera showed that the novel FPI hyperspectral technology provided accurate geometric, radiometric and sp…
Tree species recognition in species rich area using UAV-borne hyperspectral imagery and stereo-photogrammetric point cloud
2017
Abstract. Recognition of tree species and geospatial information of tree species composition is essential for forest management. In this study we test tree species recognition using hyperspectral imagery from VNIR and SWIR camera sensors in combination with 3D photogrammetric canopy surface model based on RGB camera stereo-imagery. An arboretum forest with a high number of tree species was used as a test area. The imagery was acquired from the test area using UAV-borne cameras. Hyperspectral imagery was calibrated for providing a radiometrically corrected reflectance mosaic, which was tested along with the original uncalibrated imagery. Alternative estimators were tested for predicting tree…
Laser illumination designs for snapshot multi-spectral-line imaging
2019
For multi-spectral imaging, both acquisition time of the spectral image set and the spectral bandwidth of each image have to be minimized. Ultimate performance can be achieved if the set of monochromatic (single-wavelength) spectral images is obtained with a single snapshot — a technique provisionally called "snapshot multi-spectral-line imaging" or SMSLI. Using contemporary RGB colour cameras, up to three spectral line images can be extracted from a snapshot image data cube at specific illumination that comprises only three spectral lines, each of them positioned within one of the detection bands (R, G or B) [1]. Techniques able to provide more spectral line images are under development, a…
Single snapshot RGB multispectral imaging at fixed wavelengths: proof of concept
2014
A concept of single snapshot multispectral imaging by standard RGB image sensors under spectrally-specific illumination comprising a fixed number of narrow spectral lines is discussed and experimentally validated. The limiting conditions, RGB band spectral crosstalk corrections and potential applications for parametric mapping of skin are regarded, along with the preliminary results of the proof-of-concept measurements.
Determination of chromophore distribution in skin by spectral imaging
2012
Possibilities to determine chromophore distribution in skin by spectral imaging were explored. Simple RGB sensor devices were used for image acquisition. Totally 200 images of 40 different bruises of 20 people were obtained in order to map chromophores bilirubin and haemoglobin. Possibilities to detect water in vitro and in vivo were estimated by using silicon photodetectors and narrow band LEDs. The results show that it is possible to obtain bilirubin and haemoglobin distribution maps and observe changes of chromophore parameter values over time by using a simple RGB imaging device. Water in vitro was detected by using differences in absorption at 450 nm and 950 nm, and 650 nm and 950 nm.
3×3 Technique for RGB Snapshot Mapping of Skin Chromophores
2015
Three monochromatic spectral images have been extracted from a single RGB image data set at simultaneous illumination of skin by 473nm, 532nm and 609nm spectral lines. They were further transformed into distribution maps of three skin chromophores - melanin, oxy-hemoglobin and deoxy-hemoglobin, related to pigmented and vascular skin malformations. Performance and clinical potential of the proposed 3×3 technique is discussed.
Skin chromophore mapping by modified video-microscope
2013
Possibilities to map skin chromophores using a modified low-cost digital video-microscope is discussed. The device comprises CMOS digital imaging sensor, four-colour LED illumination system and image acquisition optics. The main goal is to obtain a set of spectral images of the skin area of interest for further conversion into maps of the main skin chromophores
Photoaging evaluation by RGB images using a smartphone for photodynamic therapy assessment
2017
In this study was evaluated the photoaging of patients' skins by the processing of RGB images acquired with an optical system based on a smartphone. Two groups were approached: a younger and an older.
Tree Species Identification Using 3D Spectral Data and 3D Convolutional Neural Network
2018
In this study we apply 3D convolutional neural network (CNN) for tree species identification. Study includes the three most common Finnish tree species. Study uses a relatively large high-resolution spectral data set, which contains also a digital surface model for the trees. Data has been gathered using an unmanned aerial vehicle, a framing hyperspectral imager and a regular RGB camera. Achieved classification results are promising by with overall accuracy of 96.2 % for the classification of the validation data set. nonPeerReviewed