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Image segmentation metrics have been extensively used in the literature to compare segmentation algorithms among each other, or relative to a ground-truth segmentation. Some metrics are easy to compute (e.g., Dice, Jaccard), others are more accurate (e.g., the Hausdorff distance) and may reflect local topology, but they are computationally demanding. While certain attempts have been made to create...
In this paper we present an modified active contour model for fast multiphase image segmentation based on the piecewise constant Vese-Chan model and the split Bregman method. By applying the globally convex image segmentation technique to the piecewise constant Vese-Chan energy functional, we first define a new biconvex energy functional to guarantee fast convergence. Then we incorporate the edge...
Popular foreground-background segmentation algorithms are based of background subtraction. In complex indoor environments, if an object in motion initially remains stationary for a certain period, it can be absorbed into the background, becoming invisible to the system. Aiming at solving this problem, this paper presents a flexible and robust foreground-background segmentation algorithm based on accurate...
This paper presents a new method for evaluating and comparing image segmentation results. This method consists of an association of measures that have the purpose to compute, in the sense of segmentation evaluation, the difference between two regions, one extracted from an ideal segmentation map and the same region obtained with a segmentation algorithm. Those measures take into account many aspects...
We present a coverage segmentation method for extracting thin structures in two-dimensional images. These thin structures can be, for example, retinal vessels, or microtubules in cytoskeleton, which are often 1–2 pixels thick. There exist several methods for coverage segmentation, but when it comes to thin and long structures, the segmentation is often unreliable. We propose a method that does not...
Many microscopy images, or 3D depth maps can be represented using piecewise constant models. They usually contain noise due to sensor imperfectness. In this paper, an improved separable denoising method based on the relative intersection of confidence intervals rule is proposed. The method uses median averaging and is robust to outliers and different noise distributions. It over-performs competitive...
Two new statistical scale space methodologies are discussed. The first method aims to detect differences between two images obtained from the same object at two different instants of time. Both small scale sharp changes and large scale average changes are detected. The second method detects features that differ in intensity from their surroundings and it produces a multiresolution analysis of an image...
Traditional correlation filters are designed and implemented via the frequency domain, where the correlation of two signals may be computed efficiently. However, when the discrete Fourier transform (DFT) of length N is used, multiplication in the frequency domain results in an N-point circular correlation, rather than a linear correlation. The resulting correlation filter output is therefore corrupted...
Rotation invariance is an important property for any feature matching method and it has been implemented in different ways for different methods. The Log Polar Transform has primarily been used for image registration where it is applied after phase correlation, which in its turn is applied on the whole images or in the case of template matching, applied on major parts of them followed by an exhaustive...
With an application to the quality control of steel, we present image processing algorithms for unsupervised detection of anomalies that are hidden within a global milling pattern. Thereby, we consider global Fourier-based approaches and the localized shearlet decomposition for damping the milling texture. These frequency-based approaches are compared to template-based autocorrelation in the spatial...
In this paper, we address the problem of physical object identification based on optical non-cloneable surface microstructure images. Physical object identification is an emerging problem raised in mobile multimedia applications that interact with physical objects as well as in physical world security applications for which there is a great need for reliable, fast and secure object verification. One...
For the purpose of secure signature verification, it is preferable to use small sized feature data which is stable between genuine signatures and difficult to be mimicked by illegal transactions. Although the turning points extracted from XY position and pressure of pen is one of efficient feature data, they are not suitable for printed signatures written by Chinese or Japanese. This is because the...
In this paper we propose a novel color image retrieval technique based on Gaussian modelling of multichannel spatio-chromatic information. The query image is represented using a number of images expressing its similarity to a set of colors derived using the median cut quantization method. Having the image decomposed into multiple channels describing its similarity to image representative colors, the...
This work is made under a behavioral marketing project, and aims at identify the age band of a person from a 2D image face. A Multi-Scale and Multilevel Histogram of Blocks of Local Binary Patterns (MMHLBP) is used as texture descriptor. Three approaches are performed and compared. In the first approach, the goal is to predict the age before getting the age band. Partial Least Squares Regression and...
The authenticity and reliability of iris recognition-based biometric identification system is well-proven. Traditional iris recognition methods use expensive feature extraction algorithms and complex-valued IrisCodes that may hinder the development of a fast identification technique for multimodal biometric system. In this paper, a new set of computationally efficient real-valued features is proposed...
Internet video collections, TV shows archives, video-on-demand systems, video libraries, personal video archives offered in the Web, etc. store more and more amount of digital video data. Therefore, new methods for automatic indexing and retrieval of video data are being developed, new technologies are being proposed. Due to a huge commercial appeal the TV sports news has become one of the dominant...
In this paper we consider the problem of tracking semi-rigid objects in video sequences using particle filters, with a particular focus on hand tracking applications. Although many different feature descriptors have been developed, none of them alone is good enough to deal with this complex tracking scenarios. Approaches which use a statistical representation of the target tend to fail in presence...
In this research paper, we describe a moving object detection algorithm in video frame sequences based on interframe temporal information and marked-watershed notion in the intra-spatial domain. The algorithm begins with difference image between two adjacent frames. By applying the Canny operator to the difference image and the current video frame, we are able to confine the distance of the edge pixels...
An attentive vision method for thermal stress detection and monitoring using a multi-scale spatiotemporal attention operator is proposed for monitoring overheating in wafer-scale integrated circuits. This method represents a multi-scale and multi-temporal analysis of infrared image sequences of the inspected surfaces by an attention operator to detect feature points. Such points may indicate possible...
A critical step in multi-frame super-resolution is the registration of frames based on their motion. We improve the performance of current state-of-the-art super-resolution techniques by proposing a more robust and accurate registration as early as in the initialization stage of the high resolution estimate. Indeed, we solve the limitations on scale and motion inherent to the classical Shift &...
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