The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In this paper, an invisible watermarking algorithm for satellite imagery using Curvelet Transform is proposed. The Raster image is split into smaller non-overlapping blocks. Haralick Co-occurrence texture features [1] are used to identify the area for embedding watermark in these blocks of Raster image. Thus multiple watermarks are embedded in any given image. Edges are selected for embedding watermark...
In this paper, we propose a superpixel generation method for synthetic aperture radar (SAR) images by using the density-based spatial clustering of applications with noise (DBSCAN) algorithm. The pixels is firstly grouped to generate initial superpixels by using probabilistic patch-based (PPB) dissimilarity. Then, small clusters are combined into their neighbor superpixels to get final results through...
Detection, and localization of Bangla text from natural scene images are important prerequisites for developing Bangla OCR as well as many content-based image analyses. But there is no standard Bangla OCR to be used in the daily work. Due to the presence of some unique features, detection and localization of Bangla text have become more challenging than English text. In this paper, we have proposed...
This paper presents a computational framework for accurately estimating the disparity map of plenoptic images. The proposed framework is based on the variational principle and provides intrinsic sub-pixel precision. The light-field motion tensor introduced in the framework allows us to combine advanced robust data terms as well as provides explicit treatments for different color channels. A warping...
Traditional point tracking algorithms such as the KLT use local 2D information aggregation for feature detection and tracking, due to which their performance degrades at the object boundaries that separate multiple objects. Recently, CoMaL Features have been proposed that handle such a case. However, they proposed a simple tracking framework where the points are re-detected in each frame and matched...
Single-image blind deblurring could be considered as an important preprocessing step in imaging information fusion. Its purpose is to simultaneously estimate blur kernel and latent sharp image from only one observed blurred image. Blind deblurring has been attracting increasing attention in the fields of image processing, computer vision, computational photography, etc. However, it is a typically...
Fragment reconstruction aims to restore broken images and documents via matching spatial adjacent fragments. As the existing solutions in the literature still remain problematic, we present a novel feature descriptor, Normal Direction Local Binary Pattern (termed as ND-LBP), for document/image fragment matching. ND-LBP is based on the conventional LBP descriptor, however, it outstands LBP by introducing...
We study semi-supervised learning for image classifiers from a graph signal processing (GSP) perspective. Specifically, by viewing a binary classifier as a graph-signal in a high-dimensional feature space, we cast classifier learning as a signal restoration problem via a classical maximum a posteriori (MAP) formulation. Unlike previous graph-signal restoration works, we consider in addition edges...
Social network is becoming indispensable of people's lives in recent years. Community detection on real network continues to be a hotspot in data ming domain. As users may join multiple social circles and interest communities, and an abundance of information can be a reflection of users' preference, heterogeneous information fusion and overlapping community detection are two key issues researchers...
Nowadays, HOG (Histogram of Gradient) feature is extracted from the objects and using it in the classification tasks among the many visual application systems such as object tracking, action recognition and automated video surveillance. Most techniques of extraction HOG feature are based on cells and blocks. Although the HOG feature on cell and block are being robust for current visual systems, the...
In recent years, Unmanned Aerial Vehicle (UAV) is widely used for power lines patrol. While it's more efficient than manually patrolling, the UAV may easily collide with power lines. Therefore, measures must be taken to detect the distance between UAV and power lines. This paper presents a real-time power line detect system based on binocular vision techniques, which contains a hardware platform based...
In recent times, user activities on web-based social networks has increased enormously irrespective of time and place that generates a variety of datasets which further offers tremendous scope for both mining and knowledge discovery. Due to a large number of Social Networking websites and interactions among people via these sites, rapid growth in social networks has taken place. Community detection...
Detecting Sybils in online social networks (OSNs) is a fundamental security research problem as adversaries can leverage Sybils to perform various malicious activities. Structure-based methods have been shown to be promising at detecting Sybils. Existing structure-based methods can be classified into two categories: Random Walk (RW)-based methods and Loop Belief Propagation (LBP)-based methods. RW-based...
Traditional stereo matching approaches generally have problems in handling textureless regions, strong occlusions and reflective regions that do not satisfy a Lambertian surface assumption. In this paper, we propose to combine the predicted surface normal by deep learning to overcome these inherent difficulties in stereo matching. With the selected reliable disparities from stereo matching method...
Most visual odometry algorithm for a monocular camera focuses on points, either by feature matching, or direct alignment of pixel intensity, while ignoring a common but important geometry entity: edges. In this paper, we propose an odometry algorithm that combines points and edges to benefit from the advantages of both direct and feature based methods. It works better in texture-less environments...
We present LS-ELAS, a line segment extension to the ELAS algorithm, which increases the performance and robustness. LS-ELAS is a binocular dense stereo matching algorithm, which computes the disparities in constant time for most of the pixels in the image and in linear time for a small subset of the pixels (support points). Our approach is based on line segments to determine the support points instead...
A novel two-stage segmentation model is proposed for fast segmentation of intensity inhomogeneity images. In the first stage, the image is down-sampled and then segmented by local correntropy-based K-means clustering (LCK) method to get a coarse segmentation contour fast. In the second stage, the image is further segmented using an improved LCK method, which takes the up-sampled coarse segmentation...
It is commonly accepted that one of the most important factors for assuring the high performance of an electrical network is the surveillance and the respective preventive maintenance. From a long time ago that TSOs and DSOs incorporate in their maintenance plans the surveillance of the grid, where is included the aerial power lines inspection. Those inspections started by human patrol, including...
Cooperative target has been widely applied in vision-based navigation for unmanned aerial vehicle. For overcoming the targets susceptibility of the surroundings, a fast and accurate detection approach based on multiple features is put forward. Firstly, utilize the pyramid image preprocessing method to eliminate some noise. Then the image features consisting of image contours, Hu moment invariants...
This paper presents a robust approach for road marking detection and recognition from images captured by an embedded camera mounted on a car. Our method is designed to cope with illumination changes, shadows, and harsh meteorological conditions. Furthermore, the algorithm can effectively group complex multi-symbol shapes into an individual road marking. For this purpose, the proposed technique relies...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.