Search results for "Multimodal Image"

Multimodal Images Classification using Dense SURF, Spectral Information and Support Vector Machine

2019

International audience; The multimodal image classification is a challenging area of image processing which can be used to examine the wall painting in the cultural heritage domain. In such classification, a common space of representation is important. In this paper, we present a new method for multimodal representation learning, by using a pixel-wise feature descriptor named dense Speed Up Robust Features (SURF) combined with the spectral information carried by the pixel. For classification of extracted features we have used support vector machine (SVM). Our database was extracted from acquisition on cultural heritage wall paintings that contain four modalities UV, Visible, IRR and fluores…

Fusion of multimodal data by combining the uncertainty and perception models

2019

The general idea is to use together heterogeneous multiple information on the same problem tainted by imperfections and coming from several sources in order to improve the knowledge of a given situation. Appropriate visualization of the images to aid in decision making using the perceptual information carried by the salience maps.

Study of new tellurite glasses in the TeO2-ZnO-La2O3 (TZL) system for the manufacturing of mid-infrared multimaterial optical fibers and specialty op…

2023

This thesis work was carried out using tellurite glasses from the TeO2-ZnO-La2O3 (TZL) ternary diagram for optical fibers manufacturing. The choice to use this system is motivated by the ambition to improve the transmission of optical signals within oxide glasses for which absorption bands related to OH groups are present in the transparency window. A structural study is first carried out on these glasses by Raman spectroscopy in order to understand the influence of the composition on physicochemical properties (especially on optical and thermal properties) but also to estimate the ability of a vitreous matrix to reorganize when subjected to a thermal solicitation such as the preform-to-fib…

Improving point matching on multimodal images using distance and orientation automatic filtering

2016

International audience; Speed Up Robust Features SURF is one of the most popular and efficient methods used for image registration task. In order to achieve a correct registration, a good matching of feature point is required. However in the case of multimodal images, the high and non-linear intensity changes between different modalities led to many outliers (mismatching of detected points) and consequently a fail in the registration. Therefore, in this paper we introduce an efficient method devoted to the detection and removal of such outlier. It's based on an automatic filtering of outliers on both distance and orientation between features points. We tested our proposed method on a set of…

Benchmarking Saliency Detection Methods on Multimodal Image Data

2018

Saliency detecmage processing. Most of the work is adapted to the specific application and available dataset. The present work is about a comparative analysis of saliency detection for multimodal images dataset. There were many researches on the detection of saliency on several types of images, such as multispectral, natural, 3D and so on. This work presents a first focused study on saliency detection on multimodal images. Our database was extracted from acquisitions on cultural heritage wall paintings that contain four modalities UV, IR, Visible and fluorescence. In this paper, the analysis has been performed for many methods on saliency detection. We evaluate the performance of each metho…

Multimodal Image Segmentation for Radiation Treatment Planning

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…