0000000000371205
AUTHOR
Chao Li
showing 9 related works from this author
HDR image generation from LDR image with highlight removal
2015
The emergency of High Dynamic Range (HDR) display device impels the study of generating HDR image from Low Dynamic Range (LDR) image. Most existing generation methods apply complicated handing to highlight areas in image, which perplexes the algorithm and introduces the probability of generating artifacts. In this paper, we investigate a separated scheme: instead of sophisticated treatment to the highlight areas during expanding, the processing to the highlight areas is separated from the dynamic range expansion, which facilitates the framework and reduces the artifacts. The image quality metric shows that the separated scheme reveals more details with little artifacts compared to the algor…
Fuzzy selecting local region level set algorithm
2015
In this work, we introduced a novel localized region based level set model which is simultaneously effective for heterogeneous object or/and background and robust against noise. As such, we propose to minimize an energy functional based on a selective local average, i.e., when computing the local average, instead to use the intensity of all the pixels surrounding a given pixel, we first give a local Gaussian fuzzy membership to be a background or an object pixel to each of these surrounding pixels and then, we use the fuzzy weighted local average of these pixels to replace the traditional local average. With the graphics processing units' acceleration, the local lattice Boltzmann method is …
Automatic Acoustic Target Detecting and Tracking on the Azimuth Recording Diagram with Image Processing Methods
2019
International audience; Passive acoustic target detection has been a hot research topic for a few decades. Azimuth recording diagram is one of the most promising techniques to estimate the arrival direction of the interested signal by visualizing the sound wave information. However, this method is challenged by the random ambient noise, resulting in low reliability and short effective distance. This paper presents a real-time postprocessing framework for passive acoustic target detection modalities by using a sonar array, in which image processing methods are used to automate the target detecting and tracking on the azimuth recording diagram. The simulation results demonstrate that the prop…
Comparison of region of interest segmentation methods for video-based heart rate measurements
2018
International audience; Conventional contact photoplethysmography (PPG) sensors are not suitable in situations of skin damage or when unconstrained movement is required. As a consequence, remote photoplethysmography (rPPG) has recently emerged because it provides remote physiological measurements without expensive hardware and improves comfort for long-term monitoring. RPPG estimation methods use the spatially averaged RGB values of pixels in a Region Of Interest (ROI) to generate a temporal RGB signal. The selection of ROI is a critical first step to obtain reliable pulse signals and must contain as many skin pixels as possible with a low percentage of non-skin pixels. In this paper, we ex…
A predictive function optimization algorithm for multi-spectral skin lesion assessment
2015
The newly introduced Kubelka-Munk Genetic Algorithm (KMGA) is a promising technique used in the assessment of skin lesions. Unfortunately, this method is computationally expensive due to its function inverting process. In the work of this paper, we design a Predictive Function Optimization Algorithm in order to improve the efficiency of KMGA by speeding up its convergence rate. Using this approach, a High-Convergence-Rate KMGA (HCR-KMGA) is implemented onto multi-core processors and FPGA devices respectively. Furthermore, the implementations are optimized using parallel computing techniques. Intensive experiments demonstrate that HCR-KMGA can effectively accelerate KMGA method, while improv…
Neutrino Physics with JUNO
2016
The Jiangmen Underground Neutrino Observatory (JUNO), a 20 kton multi-purpose underground liquid scintillator detector, was proposed with the determination of the neutrino mass hierarchy as a primary physics goal. It is also capable of observing neutrinos from terrestrial and extra-terrestrial sources, including supernova burst neutrinos, diffuse supernova neutrino background, geoneutrinos, atmospheric neutrinos, solar neutrinos, as well as exotic searches such as nucleon decays, dark matter, sterile neutrinos, etc. We present the physics motivations and the anticipated performance of the JUNO detector for various proposed measurements. By detecting reactor antineutrinos from two power plan…
Embedded multi-spectral image processing for real-time medical application
2016
International audience; The newly introduced Kubelka-Munk Genetic Algorithm (KMGA) is a promising technique for the assessment of skin lesions from multi-spectral images. Using five skin parameter maps such as concentration or epidermis/dermis thickness, this method combines the Kubelka-Munk Light-Tissue interaction model and Genetic Algorithm optimization process to produce a quantitative measure of cutaneous tissue. Up to the present, variant improved KMGA implementations have been successfully realized using the recent parallel computing techniques. However, all these achievements are based on the multi-core CPUs. This results in a quite high cost and low practicability for the hardware …
Hydro-mechanical analysis of volcanic ash slopes during rainfall
2016
Rainfall-induced landslides in volcanic ashes represent a major natural hazard in many regions around the world. Owing to their loose structure, volcanic ash slopes are prone to rainfall-induced landslides. The paper presents a continuum modelling approach for the analysis of wetting-induced instability phenomena at the onset of failure in loose volcanic ash slopes. A numerical simulation of a landslide-prone volcanic slope in Costa Rica is carried out with a two-dimensional hydro-mechanical finite-element slope model. A constitutive model based on the effective stress concept extended to partially saturated conditions is used to reproduce the volcanic ash hydro-mechanical behaviour. The m…
An Embedded Solution for Multispectral Palmprint Recognition
2018
Palmprint based identification has attracted much attention in the past decades. In some real-life applications, portable personal authentication systems with high accuracy and speed efficiency are required. This paper presents an embedded palmprint recognition solution based on the multispectral image modality. We first develop an effective recognition algorithm by using partial least squares regression, then a FPGA prototype is implemented and optimized through high-level synthesis technique. The evaluation experiments demonstrate that the proposed system can achieve a higher recognition rate at a lower running cost comparing to the reference implementations.