Search results for "Signal and Image processing"
showing 10 items of 454 documents
Model and quality assessment of single image dehazing
2016
This thesis is mainly related to color imaging science, involving many disciplines, such as color image enhancement, image formation, color reproduction, optical physics, radiometry, colorimetry, image quality and psychophysics.Dehazing aims at recovering the image information degraded by light scattering, e.g. bad weather. This process is an ill-posed and a challenging problem. Although a variety of approaches have been proposed, there is still room for further improvement and standardization. In this work, we investigate the limitations of haze model in terms of accuracy of color image recovery. We address also the link between the visibility deterioration and the spectral content of the …
Design, Development and Evaluation of a System for the Detection of Aerial Parts and Measurement of Growth Indices of Bell Pepper Plant Based on Ster…
2022
During the growth of plants, monitoring them brings much benefits to the producers. This monitoring includes the measurement of physical properties, counting plants leaves, detection of plants and separation of them from weeds. All these can be done different techniques, however, the techniques are favorable that are non-destructive because plant is a very sensitive creature that any manipulation can put disorder in its growth or lead to losing leaves or branches. Imaging techniques are of the best solutions for plants growth monitoring and geometric measurements. In this regard, in this project the use of stereo imaging and multispectral data was studied. Active and passive stereo imaging …
Extraction and fusion of spectral parameters for face recognition
2011
This is the copy of journal's version originally published in Proc. SPIE 7877: http://spie.org/x10.xml?WT.svl=tn7. Reprinted with permission of SPIE. Many methods have been developed in image processing for face recognition, especially in recent years with the increase of biometric technologies. However, most of these techniques are used on grayscale images acquired in the visible range of the electromagnetic spectrum. The aims of our study are to improve existing tools and to develop new methods for face recognition. The techniques used take advantage of the different spectral ranges, the visible, optical infrared and thermal infrared, by either combining them or analyzing them separately …
Parameters analysis of FitzHugh-Nagumo model for a reliable simulation
2014
International audience; Derived from the pioneer ionic Hodgkin-Huxley model and due to its simplicity and richness from a point view of nonlinear dynamics, the FitzHugh-Nagumo model has been one of the most successful neuron / cardiac cell model. It exists many variations of the original FHN model. Though these FHN type models help to enrich the dynamics of the FHN model. The parameters used in these models are often in biased conditions. The related results would be questionable. So, in this study, the aim is to find the parameter thresholds for one of the commonly used FHN model in order to pride a better simulation environment. The results showed at first that inappropriate time step and…
Mutual-information based rate-adaptation for Multi-User TH-IR-UWB coded system
2011
In this paper we present a coding rate adaptation technique for a Time-Hopping Impulse-Radio Ultra-Wide Band (TH-IR-UWB) system assuming that the Multi-User Interference (MUI) is modeled as an additive interference noise following a Generalized Gaussian Distribution (GGD). The shape parameter induced by the GGD model is in general time-variant since it strongly depends on the essential UWB system parameters and the received signal power of the active users. In this paper, we show that the performance of a TH-IR-UWB LDPC coded system is quite independent of the GGD shape parameter when we consider the mutual information between the soft input to the decoder and the transmitted sequence, espe…
Quantification of melanin and hemoglobin in humain skin from multispectral image acquisition: use of a neuronal network combined to a non-negative ma…
2012
International audience; This article presents a multispectral imaging system which, coupled with a neural network-based algorithm, reconstructs reflectance cubes. The reflectance spectra are obtained using artificial neural-netwok reconstruction which generates reflectance cubes from acquired multispectral images. Then, a blind source separation algorithm based on Non-negative Matrix Factorization is used for the decomposition of human skin absorption spectra in its main pigments: melanin and hemoglobin. The analysis is performed on reflectance spectra. The implemented source separation algorithm is based on a multiplicative coefficient upload. The goal is to represent a given spectrum as t…
Discrete wavelet transform implementation in Fourier domain for multidimensional signal
2002
Wavelet transforms are often calculated by using the Mallat algorithm. In this algorithm, a signal is decomposed by a cascade of filtering and downsampling operations. Computing time can be important but the filtering operations can be speeded up by using fast Fourier transform (FFT)-based convolutions. Since it is necessary to work in the Fourier domain when large filters are used, we present some results of Fourier-based optimization of the sampling operations. Acceleration can be obtained by expressing the samplings in the Fourier domain. The general equations of the down- and upsampling of digital multidimensional signals are given. It is shown that for special cases such as the separab…
Normalization of T2W-MRI Prostate Images using Rician a priori
2016
International audience; Prostate cancer is reported to be the second most frequently diagnosed cancer of men in the world. In practise, diagnosis can be affected by multiple factors which reduces the chance to detect the potential lesions. In the last decades, new imaging techniques mainly based on MRI are developed in conjunction with Computer-Aided Diagnosis (CAD) systems to help radiologists for such diagnosis. CAD systems are usually designed as a sequential process consisting of four stages: pre-processing, segmentation, registration and classification. As a pre-processing, image normalization is a critical and important step of the chain in order to design a robust classifier and over…
Auto-Adaptive Trigger and Pulse Extraction for Digital Processing in Nuclear Instrumentation
2015
International audience; This paper presents a novel auto-adaptive method for pulse triggering and extraction. Pulse triggering uses a threshold that must be placed as close as possible to the noise level. We do this by means of an adaptive threshold level based on real-time noise level estimation. A dynamic estimation of the pulse length is also used for pulse selection. The proposed approach is largely insensitive to noise and enables autonomous extraction of pulses regardless of their shape, height or length. The proposed approach can be used with numerous types of detectors from an analog-to-digital converter, and can be used in conjunction with various pulse processing techniques such a…
“It Is Not the Robot Who Learns, It Is Me.” Treating Severe Dysgraphia Using Child–Robot Interaction
2021
Writing disorders are frequent and impairing. However, social robots may help to improve children's motivation and to propose enjoyable and tailored activities. Here, we have used the Co-writer scenario in which a child is asked to teach a robot how to write via demonstration on a tablet, combined with a series of games we developed to train specifically pressure, tilt, speed, and letter liaison controls. This setup was proposed to a 10-year-old boy with a complex neurodevelopmental disorder combining phonological disorder, attention deficit/hyperactivity disorder, dyslexia, and developmental coordination disorder with severe dysgraphia. Writing impairments were severe and limited his parti…