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We propose a framework for Threat Image Projection (TIP) in cargo transmission X-ray imagery. The method exploits the approximately multiplicative nature of X-ray imagery to extract a library of threat items. These items can then be projected into real cargo. We show using experimental data that there is no significant qualitative or quantitative difference between real threat images and TIP images...
The paper describes a new approach to the analysis of lighting systems, namely the lighting environment in general, with focus on luminance contrast mapping. Using the modern measuring equipment based on luminance analyzer units it is possible to transmit the obtained data from luminance maps to contrast maps. The current methods of determining contrast are too simple and can be applied only to a...
With the rapid advancement in mobile device technologies and connectivity, the use of mobile devices for visual object recognition is emerging as an application with great commercialization potentials. However, query images captured by mobile devices often suffer from various conditions such as illumination, scale, and viewpoint changes. To handle these, several detectors and descriptors have been...
We propose a contextual framework for 2D image matching and registration using an ensemble feature. Our system is beneficial for registering image pairs that have captured the same scene but have large visual discrepancies between them. It is common to encounter challenging visual variations in image sets with artistic rendering differences or in those collected over a period of time during which...
In this paper, we study some feature descriptors and detectors based on invariants type and use the most stable and robust keypoints for an efficient object detection. From many points of view local descriptors are relatively different, the way of their extraction and the type of the invariance, the goal of this paper is to examine existing feature detectors and apply the most appropriate and efficient...
We present an evaluation of standard image features in the context of long-term visual teach-and-repeat mobile robot navigation, where the environment exhibits significant changes in appearance caused by seasonal weather variations and daily illumination changes. We argue that in the given long-term scenario, the viewpoint, scale and rotation invariance of the standard feature extractors is less important...
New generation autonomous vehicles use different data fusion techniques to solve the Simultaneous Localization And Mapping (SLAM) problems in urban terrains. However, the majority of the implementations uses high-cost sensors like LIDAR to obtain a high accuracy map. In this paper, we present a method to solve this problem using sequences of stereo images. Our approach uses Local Intensity Order Pattern...
An efficient and almost automatic method for stereo pair extraction of aerial photos is proposed. There are several challenging problems that needs to be taken into consideration when creating stereo pairs from historical aerial photos. These problems are discussed and solutions are proposed in order to obtain an almost automatic procedure with as little input as possible needed from the user. The...
In this paper, we investigate the ability of humans to recognize objects using different types of edges. Edges arise in images because of several different physical phenomena, such as shadow boundaries, changes in material albedo or reflectance, changes to surface normals, and occlusion boundaries. By constructing synthetic photo realistic scenes, we control which edges are visible in a rendered image...
Scene image matching is often used for positioning of a visually navigated autonomous robot. The robot memorizes the scene as an image at each navigation point in the teaching mode, and knows being at the same position when the outside scene is matched to the image in the playback mode. The scene matching is usually accomplished by feature-based image matching methods, such as SIFT or SURF. However...
The vertical-objective-based ellipsometric microscope (VEM) is presented which can be used for real-time visualization of nm-thick lubricant films with high lateral resolution. The performance of hard disk drives (HDDs) depends on the dynamics of the nm-thick liquid lubricant films due to decrease of head-disk gap to 2 to 3 nm. The contact or near-contact head disk interface is needed to increase...
In the state-of-the-art visual object recognition, there are a number of descriptors that have been proposed for various visual recognition tasks. But it is still difficult to decide which descriptors have more significant impact on this task. The descriptors should be distinctive and at the same time robust to changes in viewing conditions. This paper evaluates the performance of two distinctive...
This paper presents a novel approach to discovering particular objects from a set of unannotated images. We aim to find discriminative feature sets that can effectively represent particular object classes (as opposed to object categories). We achieve this by mining correlated visual word sets from the bag-of-features model. Specifically, we consider that a visual word set belongs to the same object...
In this paper, a technique to design a robust feature extractor and descriptor for visual map building is proposed. The extracted features are required to be computationally attractive and invariant to image rotation, scale change and illumination. We adapted the scale invariant features transform (SIFT) algorithm for map building applications. Our main contributions are: firstly, we introduce of...
The research presented in this paper aims at developing and validating a predictive tool of individual exposure to solar Ultra-Violet (UV). UV exposure depends on ambient irradiation level and individual factors related to activity (position to the sun, clothing, duration of exposure, and other forms of sun protection). We predict exposure levels of body parts on basis of ambient irradiation levels...
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