Search results for "Computer Vision"
showing 10 items of 2353 documents
Apparence des matériaux, Vision artificielle, Inspection qualité, Reflectance Transformation Imaging
2022
Mastering the visual perception of the surfaces of manufactured products is a central issue for industry. However, in industry, the quality of surfaces is often assessed by human inspectors. Only a few specific cases use an instrumental or photometric approach. Among the photometric approaches, one of them is experiencing significant growth: Reflectance Transformation Imaging (RTI). However, this technique has limitations in terms of data acquisition and processing. The objective is therefore to correct some of these limitations in order to improve the RTI and, consequently, the visual quality control of surface conditions in industry.The current RTI systems are limited and cannot meet our …
Optimizing auditory images and distance metrics for self‐organizing timbre maps*
1996
Abstract The effect of using different auditory images and distance metrics on the final configuration of a self‐organized timbre map is examined by comparing distance matrices, obtained from simulations, with a similarity rating matrix, obtained using the same set of stimuli as in the simulations. Gradient images, which are intended to represent idealizations of physiological gradient maps in the auditory pathway, are constructed. The optimal auditory image and distance metric, with respect to the similarity rating data, are searched using the gradient method.
Accuracy of Rotational Parameters Predicted by High-Level Quantum-Chemical Calculations: Case Study of Sulfur-Containing Molecules of Astrochemical I…
2018
The accuracy of rotational parameters obtained from high-level quantum-chemical calculations is discussed for molecules containing second-row atoms. The main focus is on computed rotational constants for which two statistical analyses have been carried out. A first benchmark study concerns sulfur-bearing species and involves 15 molecules (for a total of 74 isotopologues). By comparing 15 different computational approaches, all of them based on the coupled-cluster singles and doubles approach (CCSD) augmented by a perturbative treatment of triple excitations, CCSD(T), we have analyzed the effects on computed rotational constants due to (i) extrapolation to the complete basis-set limit, (ii) …
Joint image and motion reconstruction for PET using a B-spline motion model.
2012
We present a novel joint image and motion reconstruction method for PET. The method is based on gated data and reconstructs an image together with a motion function. The motion function can be used to transform the reconstructed image to any of the input gates. All available events (from all gates) are used in the reconstruction. The presented method uses a B-spline motion model, together with a novel motion regularization procedure that does not need a regularization parameter (which is usually extremely difficult to adjust). Several image and motion grid levels are used in order to reduce the reconstruction time. In a simulation study, the presented method is compared to a recently propos…
Wavelet analysis and neural network classifiers to detect mid-sagittal sections for nuchal translucency measurement
2016
We propose a methodology to support the physician in the automatic identification of mid-sagittal sections of the fetus in ultrasound videos acquired during the first trimester of pregnancy. A good mid-sagittal section is a key requirement to make the correct measurement of nuchal translucency which is one of the main marker for screening of chromosomal defects such as trisomy 13, 18 and 21. NT measurement is beyond the scope of this article. The proposed methodology is mainly based on wavelet analysis and neural network classifiers to detect the jawbone and on radial symmetry analysis to detect the choroid plexus. Those steps allow to identify the frames which represent correct mid-sagitta…
A Novel Approach of a Low-Cost UWB Microwave Imaging System with High Resolution Based on SAR and a New Fast Reconstruction Algorithm for Early-Stage…
2022
In this article, a new efficient and robust approach—the high-resolution microwave imaging system—for early breast cancer diagnosis is presented. The core concept of the proposed approach is to employ a combination of a newly proposed delay-and-sum (DAS) algorithm and the specific absorption rate (SAR) parameter to provide high image quality of breast tumors, along with fast image processing. The new algorithm enhances the tumor response by altering the parameter referring to the distance between the antenna and the tumor in the conventional DAS matrices. This adjustment entails a much clearer reconstructed image with short processing time. To achieve these aims, a high directional Vivaldi …
Comparison of stereo vision techniques for cloud-top height retrieval
2007
This paper presents an ongoing study for the estimation of the cloud-top height by using only geometrical methods. In agreement with some recent studies showing that it is possible to achieve reliable height estimations not only with the classical methods based on radiative transfer, this article includes a comparison of performances of a selected set of vision algorithms devoted to extract dense disparity maps or motion fields from Infra Red stereo image pairs. This collection includes both area-based techniques and an optical flow-based method and the comparison is accomplished by using a set of cloudy scenes selected from the Along-Track Scanning Radiometer (ATSR2) database. The first gr…
A fully automatic approach for multimodal PET and MR image segmentation in gamma knife treatment planning
2017
The aim of this study is to combine Biological Target Volume (BTV) segmentation and Gross Target Volume (GTV) segmentation in stereotactic neurosurgery.Our goal is to enhance Clinical Target Volume (CTV) definition, including metabolic and morphologic information, for treatment planning and patient follow-up.We propose a fully automatic approach for multimodal PET and MR image segmentation. This method is based on the Random Walker (RW) and Fuzzy C-Means clustering (FCM) algorithms. A total of 19 brain metastatic tumors, undergone stereotactic neuro-radiosurgery, were retrospectively analyzed. A framework for the evaluation of multimodal PET/MRI segmentation is presented, considering volume…
EFFICIENT MACHINE LEARNING FRAMEWORK FOR COMPUTER-AIDED DETECTION OF CEREBRAL MICROBLEEDS USING THE RADON TRANSFORM
2014
International audience; Recent developments of susceptibility weighted MR techniques have improved visualization of venous vasculature and underlying pathologies such as cerebral microbleed (CMB). CMBs are small round hypointense lesions on MRI images that are emerging as a potential biomarker for cerebrovascular disease. CMB manual rating has limited reliability, is time-consuming and is prone to errors as small CMBs can be easily missed or mistaken for venous crosssections. This paper presents a computer-aided detection technique that utilizes a novel cascade of random forest classifiers which are trained on robust Radon-based features with an unbalanced sample distribution. The training …
Generalization of Canny–Deriche filter for detection of noisy exponential edge
2002
This paper presents a generalization of the Canny-Deriche filter for ramp edge detection with optimization criteria used by Canny (signal-to-noise ratio, localization, and suppression of false responses). Using techniques similar to those developed by Deriche, we derive a filter which maximizes the product of the first two criteria under the constraint of the last one. The result is an infinite length impulse response filter which leads to a stable third-order recursive implementation. Its performance shows an increase of the signal-to-noise ratio in the case of blurred and noisy images, compared to the results obtained from Deriche's filter.