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In this paper, a structural similarity index is first proposed for two images with possibly different dynamic ranges and intensities as well as possibly small rotation and translation. The proposed index is then extended by dividing two images into local windows, and the similarity is detected by checking all pairs of local windows. It is shown by experimental results that the proposed indices are...
Discriminative tracking has become popular tracking methods due to their descriptive power for foreground/background separation. Among these methods, online random forest is recently proposed and received a large amount of research attention due to its advantages such as efficiency and robustness to noise, etc. However, the fact that only one kind of features is used limits the discriminative performance...
Image based rendering is an attractive alternative for generating novel views compared to model based rendering due to its lower complexity and potential for photo-realistic results. We present a fast unsupervised method for synthesising arbitrary viewpoints of a scene from a set of existing views. Our novel improvements include optimising the placement of depth layers to take advantage of the composition...
In this paper, we propose a novel multi-resolution background subtraction method. We adopt coarse to fine strategy, which is the essence the multi-resolution scheme, to obtain the foreground mask. The rough mask is first gained relied on the Single Gaussian Model, which holds minor computation cost. Then, the slightly accuracy mask is calculated by the Saliency-based Extraction Model, which contains...
The real noise model corrupting the observed images is unknown and usually random statistical model. Consequently, classical SRR (Super Resolution Reconstruction) algorithms using median (L1) and mean (L2) filtering structures may degrade the reconstructed image sequence rather than enhance it. The mathematical analysis [1] demonstrates that the meridian filtering structure exhibits more robust characteristic...
License plate character segmentation is a crucial process of license plate recognition. During the process of image acquisition, because of light condition and the change of shooting distance and the diversity of the plate's format, the task become very challenging. Therefore, many algorithms are proposed under certain conditions, such as a fixed shooting distance or no illumination change. The purpose...
Visual marker systems have become an ubiquitous tool to supply a reference frame onto otherwise general scenes. Throughout the last decades, a wide range of different approaches have emerged, each one endowed with different strengths and limitations. Some techniques adopt tags that are optimized to reach a high accuracy in the recovered camera pose, others are based on designs that aim to maximizing...
A new method based on the Discrete Cosine Transform (DCT) and the Otsu method for blur detection in image sequences is proposed in this paper. In the first step, the standard deviation (STD) and the DCT coefficients are utilized to detect blurred and homogeneous areas in each image. Then, the Otsu method is used to calculate an adaptive threshold in each segment of the image sequence. Our experiments...
This paper presents a video watermarking technique able to resist geometric attacks. The proposed method performs imperceptible watermarking of video in the spatio-temporal domain. Before embedding or detecting the watermark in the video, the location of the most appropriate triangles used for positioning the watermark must be found. For this reason, the interest points in each frame are first found...
This paper proposes a novel image denoising algorithm in spatial domain for filtering mixture of speckle and impulse noise using combination of local statistics and non-linear Robust Estimator. Proper choice of despeckling filter is an important requirement for contrast enhancement. On the other hand suppression of impulse noise aids the enhancement and preservation of edges. The proposed algorithm...
Fuzzy C-Means (FCM) algorithm is the most popular method used in image segmentation for clustering because it has robust characteristics for ambiguity and can retain much more information than hard segmentation methods. Although the conventional FCM algorithm works well on most noise-free images, it is very sensitive to noise and other imaging artifacts, since it does not consider any information...
Digital watermarking is an effective and popular technique for discouraging illegal copying and distribution of copyrighted digital image information, which in turn provides an alternative solution for image authentication. This paper proposes an innovative watermarking scheme in which some pixels are randomly selected from original image, so that all of them have a valid 3 × 3 neighborhoods. A binary...
This paper is focus on the analysis of the ability of iris segmentation method to process images with heterogeneous characteristics, simulating the dynamics of a non-cooperative environment. Aimed to improve the performance of iris segmentation method in non-cooperative environment, the authors introduce a new method. According to the different characteristics of the inner border and outer border...
In this paper, we propose a novel image super-resolution algorithm, referred to as interpolation based on transductive regression with local and global consistency (TRLGC). Our algorithm first constructs a set of local interpolation models which can predict the intensity labels of all image samples, and a loss term will be minimized to keep the predicted labels of available low-resolution (LR) samples...
We introduce the notion of Principal Component Analysis (PCA) of image gradient orientations. As image data is typically noisy, but noise is substantially different from Gaussian, traditional PCA of pixel intensities very often fails to estimate reliably the low-dimensional subspace of a given data population. We show that replacing intensities with gradient orientations and the ℓ2 norm with a cosine-based...
We introduce a fast and robust subspace-based approach to appearance-based object tracking. The core of our approach is based on Fast Robust Correlation (FRC), a recently proposed technique for the robust estimation of large translational displacements. We show how the basic principles of FRC can be naturally extended to formulate a robust version of Principal Component Analysis (PCA) which can be...
This paper proposes a 2D face recognition algorithm using phase-based correspondence matching. The phase information obtained from 2D DFT (Discrete Fourier Transform) of images contains important information of image representation. The phase-based image matching is successfully applied to sub-pixel image registration tasks for computer vision applications and image recognition tasks for biometric...
This work introduces techniques to facilitate large-scale Augmented Reality (AR) experiences in unprepared outdoor environments. We develop a shape-based object detection framework that works with limited texture and can robustly handle extreme illumination and occlusion issues. The contribution of this work is a purely geometric approach for detecting marker-like objects under difficult and realistic...
Iterative image reconstruction for positron emission tomography (PET) can improve image quality by using spatial regularization that penalizes image intensity difference between neighboring pixels. The most commonly used quadratic penalty often over-smoothes edges and small objects in reconstructed images. Non-quadratic penalties can preserve edges but may introduce piece-wise constant blocky artifacts...
The endocardium tracking in ultrasound images is challenging due to large shape variations and the signal dropout. In this paper, we present a method to fuse multiple information sources to robustly track the endocardium. The first novelty of the method is to perform tracking in a straightened shape space, to minimize the image pattern changes caused by cardiac motions. Straightened images are used...
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