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.
This paper present a face detection system using radial basis function neural networks with variance spread value. Face detection is the first step in face recognition system. The purpose is to localize and extract the face region from the background that will be fed into the face recognition system for identification. General preprocessing approach was used for normalizing the image and a radial...
It is known that detecting small targets in remotely sensed image is difficult and challenging work. Filter neural network is designed to detect target which based morphological, structure element is used as network parameter, by competition and cooperation, network parameter is adjusted. Morphologic changed-weight neural network algorithm is used to realize small infrared target detection under complex...
Image segmentation is a primary step in many computer vision tasks. In this paper the method uses watershed algorithm based on gradient magnitude, In which the input RGB color image is transformed into HSI color space and above stated algorithm is applied on the image. Since output of watershed is oversegmented, the results based on actual implementation of adaptive color image segmentation (ACIS)...
This paper proposed a new motion detection algorithm based on neural network (NN). Video background was modeled by combing probabilistic neural network (PNN) and winner take all (WTA) network, which is called adaptive background PNN (ABPNN). Every pixel in a video frame was classified to be foreground or background by conditional probability of being a background. Foreground was further classified...
This paper describes an object detection algorithm based on pulse coupled neural networks (PCNN). To implement real time fusion of infrared surveillance object with an augmented background, the objects must be detected effectively, but the precision are not required. The simple frame difference method is adopted. We use an improved pulse coupled neural network to segment the frame difference image...
The detection of texts in video images is an important task towards automatic content-based information indexing and retrieval system. In this paper, we propose a texture-based method for text detection in complex video images. Taking advantage of the desirable characteristic of gray-scale invariance of local binary patterns (LBP), we apply a modified LBP operator to extract feature of texts. A polynomial...
A correct video segmentation, namely the detection of moving objects within a scene plays a very important role in many application in safety, surveillance, traffic monitoring and object detection. The main objective of this paper is to implement an effective background segmentation algorithm for corner sets extracted from video sequences. A dynamic prototype of the structure of background corners...
In order to decrease negative effects brought by the particularity and complexity of imaging environment, and satisfy the real-time need of the underwater task, combined invariant moments are extracted as recognition features. Furthermore, an underwater target recognition system based on neural network which improved by Artificial Fish Swarm Algorithm (AFSA) is proposed. AFSA is of capable of attaining...
Developing robust computer vision algorithms to detect fruit in trees is challenging due to less controllable conditions, including variation in illumination within an image as well as between image sets. There are two classes of techniques: local-feature-based techniques and shape-based techniques, which have been used extensively in this application domain. Out of the two classes, the local-feature-based...
Object tracking is an important application in wireless sensor network (WSN). High-accuracy and energy-efficiency are key requirements. In this paper, we propose a novel face-based object tracking protocol (FOTP), which is used to track the object with low energy consumption and high quality. FOTP combines a hexagon algorithm with face-architecture system model, which can provide precise detection...
Given a rectangle with emitters and receivers on its perimeter, one can detect objects in it by determining which of the line segments between emitters and receivers are blocked by objects. The problem of object detection can be formulated as the problem of finding all non-empty n-wedge intersections, where a wedge is defined by a consecutive set of blocked line segments from the same emitter. We...
The Top-Hat morphological filters are a class of nonlinear signal processing algorithms, which have been applied extensively to computer vision, image processing, and more recently target detection. In this paper a novel method for optimal learning of morphological filtering parameters for spot target detection is presented. We show how the genetic algorithms can be used for an automatic optimization...
Face detection is the cornerstone of a wide range of applications such as video surveillance, robotic vision and biometric authentication. One of the biggest challenges in face detection based applications is the speed at which faces can be accurately detected. In this paper, we present a novel SoC (System on Chip) architecture for ultra fast face detection in video or other image rich content. Our...
Pulse integration technology is widely used to enhance signal-noise-ratio (SNR) for moving ground target detection in Synthetic Aperture Radar and other radars systems. In this paper, the performance of pulse integration of moving targets accounting for target motion errors is analyzed. For the long dwell time condition, the effects of time-variant motion of targets are analytically discussed. The...
Detecting an aircraft solely by its infrared (IR) signature in real time can be extremely challenging task depending on the image background clutter. Neural networks offer a reliable method of detecting targets (aircraft) against a multitude of background scenes and a variety of environmental conditions. Neural networks can rapidly "learn" to differentiate between background clutter and...
In this paper, a stereo framework for a robust real time localization of objects using networkpsilas camera pairs is presented. The stereo system contains a combination of static and pan-tilt-zoom (PTZ) cameras instead of traditional dual head mounted cameras. The proposed novelty consists in applying stereo vision to heterogeneous cameras belonging to a video-surveillance network. First, a look-up-table...
In recent years there is a growing interest in the study of sparse representation for signals. This article extends this research into a novel model for object classification tasks. In this model, we first apply the non-negative K-SVD algorithm to learning the discriminative dictionaries using very few training samples and then represent a test image as a linear combination of atoms from these learned...
The land cover types in urban fringe areas are relatively complex so as to improve the classification accuracy difficultly. This article analyzes the distribution characteristic in feature space of the pixels with a local window from satellite image on a part of SPOT from an urban fringe area in Beijing. There are two methods with different input parameters of using artificial neural networks to describe...
This paper discusses a method for abnormal motion detection and its real-time implementation on a smart camera. Abnormal motion detection is a surveillance technique that only allows unfamiliar motion patterns to result in alarms. Our approach has two phases. First, normal motion is detected and the motion paths are trained, building up a model of normal behaviour. Feed-forward neural networks are...
To provide valuable services in ubiquitous and pervasive computing, it is necessary to estimate the location of users or objects in the environment. The Global Positioning System (GPS) has supported many applications using outdoor location estimation, but there is still a need for alternative technologies in buildings. Assuming that multiple wireless sensors will be attached to ubiquitous environments,...
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.