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Place recognition in 3D data is a challenging task that has been commonly approached by adapting image-based solutions. Methods based on local features suffer from ambiguity and from robustness to environment changes while methods based on global features are viewpoint dependent. We propose SegMatch, a reliable place recognition algorithm based on the matching of 3D segments. Segments provide a good...
Point-based stereo visual odometry systems typically estimate the camera motion by minimizing a cost function of the projection residuals between consecutive frames. Under some mild assumptions, such minimization is equivalent to maximizing the probability of the measured residuals given a certain pose change, for which a suitable model of the error distribution (sensor model) becomes of capital importance...
This paper present results of on-line control loop performance assessment using non-Gaussian statistical and fractal measures. Research shows importance of loop quality indexes that are not biased with Gaussian assumption about signal characteristics. Industrial data show frequent fat-tail properties and thus relevant indexes are proposed, like non-Gaussian statistical factors or persistence fractal...
The current paper proposes a novel scheme for non-blind watermarking of images, making use of discrete wavelet transform (DWT), discrete time Fourier transform (DTFT), as well as singular value decomposition, or SVD. During the process of embedding, 1-level DWT is used to decompose the host image into its various frequency sub-bands. After this, the high-frequency sub band receives an application...
This paper proposes a novel inherently rotation invariant local descriptor which combined intensity information and gradient information of key feature. The CS-LBP shows a better performance than SIFT and do not need large computation. To further enhance its performance and robustness, we calculated the gradient of key feature and computed a combined histogram included intensity and gradient information...
Retinal Neovascularization (NV) is a critical stage of Diabetic Retinopathy (DR) and its detection is important to prevent blindness. Existing fully supervised frameworks typically take a patch-based approach and report good results only on limited number of images due to sparsity of annotated data. We propose a patch-based semi-supervised framework which paves the way for including unlabeled data...
Object tracking is a critical task in surveillance and activity analysis. One main issue in tracking is illumination variation. We propose a method which is robust to illumination by incorporating a feature that is less variant to illumination. The proposed feature is a reflectance histogram obtained using sparsity constrained non-negative matrix factorization (NMFsc). Using NMFsc, illumination and...
This paper presents an improved reversible data hiding algorithm using digital images based on the histogram shifting technique. Proposed method can accurately recover the original image and extract the hidden data accurately. The highest two peak values of the host image's histogram are selected for data hiding. This embedding process is repeated again and again, to attain larger embedding capacity...
In this paper; we propose new method named local full-directional pattern (LFDP) for content-based image retrieval (CBIR). In addition, instead of applying the algorithm to the image itself, we apply it to a new image constructed by getting mean of 3×3 sub-regions gray value as each pixel's value. In local binary patter (LBP) the gray value difference of the central pixel and its neighboring pixels...
This paper proposes a novel facial image representation Block-based Local Contrast Patterns (BLCP) for illumination-robust face recognition. This method is based on an effective texture descriptor local contrast patterns (LCP). We use the directed and undirected difference masks to calculate three types of local intensity contrasts: directed, undirected, and maximum difference responses. These response...
In this paper, we propose a robust descriptor named as multiple gradient-related features (MGRF) in virtue of local and overall order encoding. Specifically, three types of features are introduced, including multidirectional gradient, gradient orientation, and first derivative of gradient orientation, each of which represents different aspect of region of interest (ROI). To extract these features,...
Contactless respiration monitoring using Doppler radar is an important technology for healthcare applications. The radar measures small displacements of the body surface. In this study, we propose a new algorithm to separate multiple targets placed closely together at the same range but at different lateral positions using ultra-wideband array radar and the Capon method. The Capon method, which is...
The performance of local descriptors such as SIFT drops under severe illumination changes. In this paper, we propose a Discriminative and Contrast Invertible (DCI) local feature descriptor. In order to increase the discriminative ability of the descriptor under illumination changes, a Laplace gradient based histogram is proposed. Moreover, a robust contrast flipping estimate is proposed based on the...
In this paper, we propose a new texture descriptor, scale selective extended local binary pattern (SSELBP), to characterize texture images with scale variations. We first utilize multi-scale extended local binary patterns (ELBP) with rotation-invariant and uniform mappings to capture robust local microand macro-features. Then, we build a scale space using Gaussian filters and calculate the histogram...
We present the performance of three popular image feature extraction methods such as Scale Invariant Feature Transformation (SIFT), Speeded-Up Robust Features (SURF) and Histogram of Oriented Gradient (HOG). Specifically, we compare the performance of feature detection methods for images corrupted with different types of noise. The efficiency of three methods are measured by considering number of...
Steganography is a branch of computer science where original information bits are to be transmitted on some carrier file[1][7]. This carrier file may be audio file, video file or image file etc. Here in this proposed work, instead of embedding a source image in a carrier image, only stego key is generated on sender side and transmitted on the channel, with some logic this source image is reconstructed...
In this paper, a variation in the Local Binary Pattern (LBP) called Modified Dominant Directional LBP (MDDLBP) is proposed. In this method, the direction of the feature with respect to its central pixel in the LBP is preserved by comparing the neighborhood of the pixel in the four dominant directions such as horizontal, vertical, diagonal and anti diagonal. This method captures complete structure...
In Direction-of-Arrival (DOA) estimation for multiple sources, removal of noisy data points from a set of local DOA estimates increases the resulting estimation accuracy, especially when there are many sources and they have small angular separation. In this work, we propose a post-processing technique for the enhancement of DOA extraction from a set of local estimates using the consistency of these...
LSB substitution steganography only takes the least significant bits in the carrier into account, which has the problems of low security and poor robustness. This paper proposes a self-contained steganography combining the MSB matching and LSB substitution. It contains two types of encoding rules to define the matching result between the secret information binary stream and the most two-significant-bit...
Existing image steganographic methods lack in the complexity, which can be utilized by the radical to decode the images and neutralize the operations. Several methods have been proposed in order to combat this. Perhaps the most efficient method is Block-based Edge Adaptive based on Least-Significant-bit Matched Revisited (LSBMR) approach. It is a famous type of steganographic methods in the spatial...
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