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This paper introduces a novel secure channel selection rule for spatial image steganography. In this scheme, there are two factors considered to identify a pixel, which causes less distortion to cover image, to be modified in data hiding. The first one is an average difference between considered pixel and its neighbors. The value of the considered pixel is the second employed factor. Obtained experimental...
In this paper we propose an efficient approach for circular shape target recovery. The method makes use of the conterminous set of edge segments, or contour segments, instead of the huge edge points as traditional detectors do. First, the proposed approach computes the contour in a given image, which is then converted into contour segments at high curvature points. Then, by calculating the reinforcement...
Safety inspection for high-rise structures should be done regularly for follow-up test. However, as it is very dangerous job and direct manual examination takes a lot of time and money, its correct diagnosis is difficult. In this paper, computer vision-based structural safety inspection system is proposed to be designed. The proposed system is an image recognition monitoring system through wireless...
This paper proposes an original approach to the problem of change detection into multitemporal image series. A primal sketch of the image is achieved with a modified Perona-Malik filter: relevant edges are extracted. Then, an application to change detection is proposed. The algorithm related to sketch outputs is performed through density of pixels images. It offers significant information about events...
This paper describes a method which uses Lapped orthogonal transform (LOT) domain adaptive enhanced Lee filter for despeckling SAR images. Since LOT is block transform, the transform coefficients are first remapped into octave type form and then the enhanced Lee filtering is applied to subband LOT coefficients. The motivation of using Lapped transform lies in its ability to preserve oscillatory type...
This paper addresses the problem of change detection from very high resolution remotely sensed images and its application on road damage extraction in case of major disaster. The proposed methodology is based on the multiscale image segmentation using the Haar wavelet in order to define the appropriate unit of analysis for the comparison step. The Kullback-Leibler divergence is then applied as a similarity...
Cracks are the most requiring type of pavement distresses to detect and classify automatically. Due to its nature are easily absorbed by other types of pavement surface damages. Moreover, the diversity of pavement surface makes the image detection system requiring efficient computer algorithms. The paper presents the solutions tested on surface distress data which were collected automatically using...
We have proposed a new speckle filtering method in this paper. Our method uses time-series of SAR images at the same scene to perform multitemporal speckle filtering to reduce speckle noise while preserving its spatial information. We used segmentation based on the distribution of speckle noise by the Öztürk algorithm in this method for achieve a higher quality of edge areas.
We propose a new method for fitting an ellipse to a point sequence extracted from an image. This method can fit an ellipse if a point sequence consists of elliptic arcs and non-elliptic arcs such as line segments. Assuming that input points are spatially connected, we iteratively select inlier points and fit an ellipse to them by computing curvatures of the residual graph. By using simulated data...
This paper presents a novel outlier removal method which is capable of fitting ellipse in real-time under high outlier rate, based on the phenomenon that outliers generated by ellipse edge point detector are likely to appear as groups due to real-world nuisances, such as under partial occlusion or illumination change. To confront the grouped outliers while maintaining the fitting efficiency, we introduce...
This paper deals with development of Robust Moving Object Detection method using Visible Spectrum and Thermal Imaging. If we fuse visible spectrum and Thermal imaging together, more information about the moving object can be obtained as both are inherently complementary to each other. The segmentation of moving objects in corresponding video frames involves ‘Background Subtraction’ method. Here each...
The term Curvelet transform in the field of Image Processing is quite well known from past few years. Its ability to detect curved features and smooth areas in an image marks its huge importance in the area of image denoising. However the ability to denoise image depends upon the selection and application of threshold after doing Curvelet based decomposition of an image. In this paper we are presenting...
Estimating the ground plane is often one of the first steps in geometric reasoning processes as it offers easily accessible context knowledge. Especially unconstrained platforms that capture video from egocentric viewpoints can benefit from such knowledge in various ways. A key requirement here is keeping orientation, which can be greatly achieved by keeping track of the ground. We present an approach...
Ultrasound (US) imaging is widely used in clinical diagnostics as it is an economical, portable, painless, comparatively safe, and non-invasive real-time tool. However, the image quality of US imaging is severely affected by the presence of speckle noise during the acquisition process. It is essential to achieve speckle-free high resolution US imaging for better clinical diagnosis. In this paper,...
In this paper, an innovative method is proposed for both noise repression and edge preservation. This method is distinct in that the structure tensor is applied in wavelet domain to detect the edge information. And both the shrinkage and the detection process are quantified and unified in the form of the matrix mask. In this way, the image denoising can be conducted with the detailed information maintained...
Medical imaging suffers from image noise. To remove this noise spatial domain and transform domain techniques are used. But spatial domain techniques have limitation of edge blurring w.r.t transform based techniques. Therefore in this paper we have proposed a transform based denoising technique. We have used Dual tree DWT and Rotated version of Dual Tree DWT jointly to improve our denoising results...
Total generalized variation (TGV) is a generalization of total variation (TV). This method has gained more and more attention in image processing due to its capability of reducing staircase effects. As the existence of high order regularity, TGV tends to blur edges, especially when noise is excessive. In this paper, we propose an iterative weighted total generalized variation (WTGV) model to reconstruct...
Underwater image segmentation is a key step for the analysis of the underwater target as segmentation quality will directly affect the stability and reliability of target recognition and tracking. A novel segmentation method is proposed in this paper that can help to solve the edge expansion and contour deformation problems in traditional segmentation methods. Firstly, the dark channel prior algorithm...
Multimodal medical image fusion plays a crucial role in medical diagnostics and treatment. Widely used transform domain based image fusion methods like DWT, CVT, CT, NCST suffer from spatial inconsistency and high complexity. Recently proposed guided filter based spatial domain image fusion techniques are also limited by contrast reduction and halo artifacts. In this paper, the existing guided filter...
The problem of source separation in two dimensions is studied in this paper. The problem is formulated in the Bayesian framework. The sources are modelled as MRFs to accommodate for the spatially correlated structure of the sources, which we exploit for separation in 2D. The difficulty of working analytically with general Gibbs distributions is overcome by using an approximate density. In this work,...
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