Search results for "RGB"
showing 10 items of 116 documents
Optimized Class-Separability in Hyperspectral Images
2016
International audience; Image visualization techniques are mostly based on three bands as RGB color composite channels for human eye to characterize the scene. This, however, is not effective in case of hyper-spectral images (HSI) because they contain dozens of informative spectral bands. To eliminate redundancy of spectral information among these bands, dimensionality reduction (DR) is applied while at the same trying to retain maximum information. In this paper, we propose a new method of information-preserved hyper-spectral satellite image visualization that is based on fusion of unsupervised band selection techniques and color matching function (CMF) stretching. The results show consist…
Individual Tree Detection and Classification with UAV-Based Photogrammetric Point Clouds and Hyperspectral Imaging
2017
Made available in DSpace on 2018-12-11T17:11:58Z (GMT). No. of bitstreams: 0 Previous issue date: 2017-03-01 Suomen Akatemia Small unmanned aerial vehicle (UAV) based remote sensing is a rapidly evolving technology. Novel sensors and methods are entering the market, offering completely new possibilities to carry out remote sensing tasks. Three-dimensional (3D) hyperspectral remote sensing is a novel and powerful technology that has recently become available to small UAVs. This study investigated the performance of UAV-based photogrammetry and hyperspectral imaging in individual tree detection and tree species classification in boreal forests. Eleven test sites with 4151 reference trees repr…
Tree Species Classification of Drone Hyperspectral and RGB Imagery with Deep Learning Convolutional Neural Networks
2020
Interest in drone solutions in forestry applications is growing. Using drones, datasets can be captured flexibly and at high spatial and temporal resolutions when needed. In forestry applications, fundamental tasks include the detection of individual trees, tree species classification, biomass estimation, etc. Deep neural networks (DNN) have shown superior results when comparing with conventional machine learning methods such as multi-layer perceptron (MLP) in cases of huge input data. The objective of this research is to investigate 3D convolutional neural networks (3D-CNN) to classify three major tree species in a boreal forest: pine, spruce, and birch. The proposed 3D-CNN models were emp…
Developing an orientation and cutting point determination algorithm for a trout fish processing system using machine vision
2019
Abstract Fish processing in small and medium fish supplying centers requires an intelligent system to operate on different sizes. Therefore, an image processing algorithm was developed to extract the proper head and belly cutting points according to the trout dimensions. The algorithm detects the fish orientation and location of pectoral, anal, pelvic, and caudal fins. In this study, each of the trout images was divided into slices along its length in order to segment the fins and extract cutting points. The channel ‘B’ of RGB color space was considered in both initial segmentation and fin detection stages among the examined channels of RGB, HSV, and L*a*b* color spaces. The back-belly and …
Three-Dimensional Integral-Imaging Display From Calibrated and Depth-Hole Filtered Kinect Information
2016
We exploit the Kinect capacity of picking up a dense depth map, to display static three-dimensional (3D) images with full parallax. This is done by using the IR and RGB camera of the Kinect. From the depth map and RGB information, we are able to obtain an integral image after projecting the information through a virtual pinhole array. The integral image is displayed on our integral-imaging monitor, which provides the observer with horizontal and vertical perspectives of big 3D scenes. But, due to the Kinect depth-acquisition procedure, many depthless regions appear in the captured depth map. These holes spread to the generated integral image, reducing its quality. To solve this drawback we …
Design and Calibration of a Specialized Polydioptric Camera Rig
2017
International audience; It has been observed in the nature that all creatures have evolved highly exclusive sensory organs depending on their habitat and the form of resources availability for their survival. In this project, a novel omnidirectional camera rig, inspired from natural vision sensors, is proposed. It is exclusively designed to operate for highly specified tasks in the field of mobile robotics. Navigation problems on uneven terrains and detection of the moving objects while the robot is itself in motion are the core problems that omnidirectional systems tackle. The proposed omnidirectional system is a compact and a rigid vision system with dioptric cameras that provide a 360° f…
Color constancy in dermatoscopy with smartphone
2017
The recent spread of cheap dermatoscopes for smartphones can empower patients to acquire images of skin lesions on their own and send them to dermatologists. Since images are acquired by different smartphone cameras under unique illumination conditions, the variability in colors is expected. Therefore, the mobile dermatoscopic systems should be calibrated in order to ensure the color constancy in skin images. In this study, we have tested a dermatoscope DermLite DL1 basic, attached to Samsung Galaxy S4 smartphone. Under the controlled conditions, jpeg images of standard color patches were acquired and a model between an unknown device-dependent RGB and a device independent Lab color space h…
Noncontact monitoring of vascular lesion phototherapy efficiency by RGB multispectral imaging.
2013
A prototype low-cost RGB imaging system consisting of a commercial RGB CMOS sensor, RGB light-emitting diode ring light illuminator, and a set of polarizers was designed and tested for mapping the skin erythema index, in order to monitor skin recovery after phototherapy of vascular lesions, such as hemangiomas and telangiectasias. The contrast of erythema index (CEI) was proposed as a parameter for quantitative characterization of vascular lesions. Skin recovery was characterized as a decrease of the CEI value relative to the value before the treatment. This approach was clinically validated by examining 31 vascular lesions before and after phototherapy.
Motion sensors for activity recognition in an ambient-intelligence scenario
2013
In recent years, Ambient Intelligence (AmI) has attracted a number of researchers due to the widespread diffusion of unobtrusive sensing devices. The availability of such a great amount of acquired data has driven the interest of the scientific community in producing novel methods for combining raw measurements in order to understand what is happening in the monitored scenario. Moreover, due the primary role of the end user, an additional requirement of any AmI system is to maintain a high level of pervasiveness. In this paper we propose a method for recognizing human activities by means of a time of flight (ToF) depth and RGB camera device, namely Microsoft Kinect. The proposed approach is…
Machine learning for rapid mapping of archaeological structures made of dry stones – Example of burial monuments from the Khirgisuur culture, Mongoli…
2020
11 pages; International audience; The present study proposes a workflow to extract from orthomosaics the enormous amount of dry stones used by past societies to construct funeral complexes in the Mongolian steppes. Several different machine learning algorithms for binary pixel classification (i.e. stone vs non-stone) were evaluated. Input features were extracted from high-resolution orthomosaics and digital elevation models (both derived from aerial imaging). Comparative analysis used two colour spaces (RGB and HSV), texture features (contrast, homogeneity and entropy raster maps), and the topographic position index, combined with nine supervised learning algorithms (nearest centroid, naive…