Magnier Baptiste

Université de Montpellier | UM1 · EuroMov Digital Health in Motion, Univ Montpellier, IMT Mines Ales, Ales, France

The investigation of the complicated underground life via automatic technique is in high demand in recent days. Using Convolutional Neural Network (CNN) to detect soil in- vertebrates is an interesting approach, although most studies on the topic have focused on other solutions. The creation of state-of-the-art technique through this work will be a...

The investigation of the complicated underground life via automatic technique is in high demand in recent days. Using Convolutional Neural Network (CNN) to detect soil invertebrates is an interesting approach, although most studies on the topic have focused on other solutions. The creation of state-of-the-art technique through this work will be a s...

Multi-modality 3D medical images play an important role in the clinical practice. Due to the effectiveness of exploring the complementary information among different modalities, multi-modality learning has attracted increased attention recently, which can be realized by Deep Learning (DL) models. However, it remains a challenging task for two reaso...

Automated and accurate classification of Whole Slide Image (WSI) is of great significance for the early diagnosis and treatment of cancer, which can be realized by Multi-Instance Learning (MIL). However, the current MIL method easily suffers from over-fitting due to the weak supervision of slide-level labels. In addition, it is difficult to disting...

Keypoint(s) or corners, as a stable feature possessing the defined characteristics of a robust point of interest, remain an active research field for machine vision researchers due to its applications in motion capture, image matching, tracking, image registration, 3D reconstruction, and object recognition. There exist different techniques for keyp...

The purpose of this paper is to find the best way to track human subjects in fisheye images by considering the most common similarity measures in the function of various color spaces as well as the HOG. To this end, we have relied on videos taken by a fisheye camera wherein multiple human subjects were recorded walking simultaneously, in random dir...

The importance and relevance of digital-image forensics has attracted researchers to establish different techniques for creating and detecting forgeries. The core category in passive image forgery is copy–move image forgery that affects the originality of image by applying a different transformation. In this paper, a frequency-domain image-manipula...

Among the common image structures, line feature is the extensively used geometric structure for various image processing applications, including the analysis of biomedical image with blood vessels highlighting, graph-shape structures, cracks detection, satellite images or remote sensing data. Multi-scale processing of line feature is essentially re...

Increasing demand for safety and security of people has resulted in more research on intelligent visual surveillance in a wide range of applications, such as moving human detection, human tracking, motion segmentation, human activity recognition , etc. With the great success of deep learning methods, researchers decided to switch from traditional m...

Fisheye cameras produce panoramic images. For a while, classical people detection algorithms were not optimal in fisheye images because detection bounding boxes were non-oriented. People detection algorithms for top view fisheye images have been developed recently. However, these algorithms only detect the people present in the different frames but...

The growing demand for liver transplantation is leading medicine to explore new technologies in order to extend the field of viable transplants. Automatic hepatic steatosis assessment is the first step towards the development of a computer-aided liver diagnosis due to its importance as a risk factor for primary dysfunction. Color and texture are co...

Visual tracking has received much attention in recent years, especially pedestrian tracking. People tracking represents an important computer vision problem with numerous real-world applications. While significant progress has been achieved for human tracking and detection, trackers are still prone to failures and inaccuracies to master all difficu...

Abstract—Ridges (resp., valley) are the useful geometric features due to their wide varieties of applications, mainly in image analysis problems such as object detection, image segmentation, scene understanding, etc. Many characterizations have contributed to formalize the ridge notion. The signification of each characteri- zation rely however on i...

Ridges and valleys are the principle geometric features for their diverse applications, especially in image analysis problems such as segmentation, object detection, etc. Numerous characterizations have contributed to formalize the ridge and valley theory. The significance of each characterization rely however on its practical usefulness in a parti...

This paper presents a new, normalized measure for assessing a contour-based object pose. Regarding binary images, the algorithm enables supervised assessment of known-object recognition and localization. A performance measure is computed to quantify differences between a reference edge map and a candidate image. Normalization is appropriate for int...

This paper introduces a new normalized measure for the assessment of a contour-based object pose. This algorithm allows a supervised assessment of recognition and localization of known objects, the differences between a reference edge map and a candidate image are quantified by computing a performance measure. This measure is normalized and is able...

Quantitative design and evaluation of enhancement/thresholding edge detectors," The normalization remains valuable to compare a set of algorithms more easily. The most frequently normalized measures of dissimilarity are described here. Each measure computes a score of quality; the closer to 1 the score of the evaluation is, the more the segmentatio...

Usually, the most important structures in an image are extracted by an edge detector. Once extracted edges are binarized, they represent the shape boundary information of an object. For the edge-based localization/matching process, the differences between a reference edge map and a candidate image are quantified by computing a performance measure....

Shock filter represents an important family in the field of nonlinear Partial Differential Equations (PDEs) models for image restoration and enhancement. Commonly, the smoothed second order derivative of the image assists this type of method in the deblurring mechanism. This paper presents the advantages to insert information issued of oriented hal...

Easy to use, oriented half kernels are reliable in image analysis. These thin filters, rotated in all the desired directions are useful to detect edges, or extract precisely their orientations, even concerning highly noisy images. Usually, the filtering process corresponds to convolutions with Gaussians and their derivatives. Other filters exist an...

Useful for human visual perception, edge detection remains a crucial stage in numerous image processing applications. One of the most challenging goals in contour detection is to operate algorithms that can process visual information as humans require. To ensure that an edge detection technique is reliable, it needs to be rigorously assessed before...

In digital images, edges characterize object boundaries, so edge detection remains a crucial stage in numerous applications. To achieve this task, many edge detectors have been designed, producing different results, with various qualities of segmentation. Indeed, optimizing the response obtained by these detectors has become a crucial issue, and ef...

Proceedings of the 8th International Conference, ICISP 2018, Cherbourg, France, July 2-4, 2018

Useful for the visual perception of a human, edge detection remains a crucial stage in numerous image processing applications. Therefore, one of the most challenging goals in contour extraction is to operate algorithms that can process visual information as humans need. Hence, to ensure that it is reliable, an edge detection technique needs to be s...

Edge detection remains a crucial stage in numerous image processing applications. Thus, an edge detection technique needs to be assessed before use it in a computer vision task. As dissimilarity evaluations depend strongly of a ground truth edge map, an inaccurate datum in terms of localization could advantage inaccurate precise edge detectors or/a...

This communication presents a new edge detection overall evaluation. Comparing the ground truth contour image and the candidate boundary image, the proposed algorithm is based upon a new criterion that takes into account the list of ground truth, the recall and their associated spacial nearness.

In recent years, information security has received a great deal of attention. To give an example, steganography techniques are used to communicate in a secret and invisible way. Digital color images have become a good medium for digital steganography because of their easy manipulation as carriers via Internet, e-mails, or used on websites. The main...

Crest line extraction remains a hard task in image processing. Indeed, these roof edges represent narrow edges on the image surface and whatever undesirable pixel close to or on the crest line may disturb the detection. This communication presents a new crest line detection overall evaluation. Comparing the ground truth contour image and the candid...

This article deals with color images steganalysis based on machine learning. The proposed approach enriches the features from the Color Rich Model by adding new features obtained by applying steerable Gaussian filters and then computing the co-occurrence of pixel pairs. Adding these new features to those obtained from Color-Rich Models allows us to...

This paper introduces the new and powerful image patch descriptor based on second order image statistics/derivatives. Here, the image patch is treated as a 3D surface with intensity being the 3rd dimension. The considered 3D surface has a rich set of second order features/statistics such as ridges, valleys, cliffs and so on, that can be easily capt...

In this paper, we present a new image patch descriptor for object detection and image matching. The descriptor is based on the standard HoG pipeline. The descriptor is generated in a novel way, by embedding the response of an oriented anisotropic derivative half Gaussian kernel in the Histogram of Orientation Gradient (HoG) framework. By doing so,...

Digital images, especially color images, are very widely used, as well as traded via Internet, e-mail and posting on websites. Images have a large size which allows embedding secret messages of large size, so they are a good medium for digital steganography. The main goal of steganalysis is to detect the presence of hidden messages in digital media...

Digital images, especially color images, are very widely used, as well as traded via Internet, e-mail and posting on websites. Images have a large size which allows embedding secret mes- sages of large size, so they are a good medium for digital steganography. The main goal of steganalysis is to detect the presence of hidden messages in digital med...

Crest line extraction has always been a challenging task in image processing and its applications. It is possible to detect ridges and valleys in images using second order filters. In order to estimate crest lines of variable widths, a multi-scale analysis of the image is required. In this paper we propose a new ridge/valley detection method in ima...

Nonlinear PDEs (partial differential equations) offer a convenient formal framework for image regularization and are at the origin of several efficient algorithms. In this paper, we present a new approach which is based (i) on a set of half Gaussian kernel filters, and (ii) a nonlinear anisotropic PDE diffusion. On one hand, half Gaussian kernels p...

This paper is dedicated to a brain magnetic resonance images regularization method, preserving grey/white matter edges using rotating smoothing filters. After a preprocessing, the originality of this approach resides in the mixing of ideas coming both from pixel classification which determines roughly if a pixel belongs to a homogenous region or an...

In this paper, a shock-diffusion model is presented to restore both blurred and noisy image. The proposed approach uses a half smoothing kernel to get the precise edge directions, and use different shock-diffusion strategies for different image regions. Experiment results on real images show that the proposed model can effectively eliminate noise a...

In this paper, we present a new color image regularization method using a rotating smoothing filter. This approach combines a pixel classification method, which roughly determines if a pixel belongs to a homogenous region or an edge with an anisotropic perceptual edge detector capable of computing two precise diffusion directions. Using a now class...

This paper is dedicated to a new anisotropic diffusion approach for image regularization based on a gradient and two diffusion directions obtained from half Gaussian kernels. This approach results in smoothing an image while preserving edges. From an anisotropic edge detector, built of half Gaussian derivative kernels, we introduce a new smoothing...

In this paper we propose a new junctions ridges and valleys detection method in images based on the dif-ference of rotating Gaussian semi filters. The novelty of this approach resides in the mixing of ideas coming both from directional filters and DoG method. We obtain a new ridges/valleys junctions anisotropic DoG detector enabling very precise de...

In this paper, we present a new image regularization method using a rotating smoothing filter. The novelty of this approach resides in the mixing of ideas coming both from pixel classification which determines roughly if a pixel belongs to a homogenous region or an edge and an anisotropic perceptual edge detector which computes two precise diffusio...

In this paper we propose a new edge detector based on anisotropic linear filtering, local maximization and gamma correction. The novelty of this approach resides in the mixing of ideas coming both from directional recursive linear filtering and gamma correction. A peculiarity of our anisotropic edge detector is that it is based on the use of two el...

In this paper we propose a new ridge/valley detection method in images based on the difference of rotating Gaussian semi filters. The novelty of this approach resides in the mixing of ideas coming both from directional filters and DoG method. We obtain a new ridge/valley anisotropic DoG detector enabling very precise detection of ridge/valley point...

In this paper we propose a new perceptual curve detection method in images based on the difference of half rotating Gaussian filters. The novelty of this approach resides in the mixing of ideas coming both from directional filters, perceptual organization and DoG method. We obtain a new anisotropic DoG detector enabling very precise detection of pe...

In this paper, we present a new method for removing texture in images using a smoothing rotating filter. From this filter, a bank of smoothed images provides pixel signals able to classify a pixel as a texture pixel, a homogenous region pixel or an edge pixel. Then, we introduce a new method for anisotropic diffusion which controls accurately the d...

In this paper, we present a new method for removing texture in color images using a smoothing rotating filter. From this filter, a bank of smoothed images provides pixel signals for each channel image able to classify a pixel belonging to a texture region. We apply this classification in each channel image in order to compute two directions for the...

In this paper we propose a new perceptual edge detector based on anisotropic linear filtering and local maximization. The novelty of this approach resides in the mixing of ideas coming both from perceptual grouping and directional recursive linear filtering. We obtain new edge operators enabling very precise detection of edge points which are invol...

This article presents a new method for estimating the pose of para-catadioptric vision systems. It is based on the estimation of vanishing points associated with vertical edges of the environment. However, unlike classical approaches no feature (line, circle) extraction and/or identification is needed. A sampled domain of possible vanishing points...