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Underwater video intelligent monitoring system extracts moving objects in a complex and dynamic scene with the impact of wave, illumination changes and reflection, while needs real-time character. To solve these situations, underwater moving object detection algorithm based on codebook model was presented. The algorithm creates a background codebook for each pixel according to color distortion and...
Due to a variety of strong noises on high-frequency surface wave radar, the real-time and accuracy of ship targets detection at sea are seriously affected. As the surface wave radar is mostly affected by the ionospheric clutter and sea clutter, a model of radar target detection system with multiplicative noise is established to characterize the effect of the two kinds of clutters on the ship target...
In this paper we present an efficient system for real-time RGB-D camera data processing on GPU architecture. Its goal is to improve the depth data accuracy while processing the RGB-D data stream in real time, thus being very attractive for depth-based interactive applications such as gesture recognition for human-computer interaction, 3D scene modeling, etc. The proposed system performs a pixel-wise...
This paper describes an efficient approach for irregular moving object detecting and tracking in real-time system based on color and shape information of the target object from realistic environment. Firstly, the data is gotten from a real-time camera system at a stable frame rate. And then, each frame is processed by using proposed method to detect and track the target object immediately in consecutive...
Target Detection involves the task of identifying and zeroing in on those set of pixels of an image that contain the required information (target). It has potential applications in diverse fields including automatic surveillance of large areas, illegal vehicle movement tracking in remote areas etc. This technique poses many challenges in terms of retaining only the target pixels by identifying and...
Foreground extraction and moving object detection are often used in human tracking systems. However those methods are not able to produce accurate results when objects are too close or when occlusions happen since the result is generally a single big blob which contains all the different objects. In this paper we propose a novel and efficient moving object detection enhancement method. Indeed, by...
According to the needs of dim and small targetdetection, a new detection algorithm based on wavelet transform and image fusion is put forward in the paper. In this algorithm, firstly, the original image is decomposed and reconstructed by wavelet and it is separated into a low frequency image and some high frequency images., secondly, the low frequency image is removed and the high frequency images...
We propose a novel object detection approach that combines the discriminative power of object category classifiers with a simple pixel level focus of attention mechanism. The pixel-level foreground/background detectors evolve to classify each pixel as either being part of an object of interest or noise. Unlike background subtraction algorithms, the decision of what is foreground is influenced by object...
It is very difficult to detect the small target over water in the marine environment because of the complexity of water movement and the complex physical fields produced by the water interact with environment. We mainly study foreground segmentation for small target in visual image based on MRF (Markov Random Fields). A foreground segmentation method is proposed that is based on kernel function and...
Smart CCTV (Closed-Circuit Television) technology has increasingly been developed in the last few years to judge the situation and notify the administrator or take immediate action for security and surveillance reasons. Currently the methods to detect object motion typically include the Frame Difference Method (FDM) which can detect moving objects and the Background Subtraction Method (BSM) which...
Image co-occurrence has shown great powers on object classification because it captures the characteristic of individual features and spatial relationship between them simultaneously. For example, Co-occurrence Histogram of Oriented Gradients (CoHOG) has achieved great success on human detection task. However, the gradient orientation in CoHOG is sensitive to noise. In addition, CoHOG does not take...
This study proposes a method to detect and mark the target object removed from the monitoring scene and the unknown object left in the monitoring scene. The present method uses the timeliness background to extract the foreground object and to mask the part that was unwanted. The foreground object was compared with the current frame, thus, the unreliable pixels were filtered out. By the identification...
This paper presents a method for target detection and tracking of IR images in the application of avian surveillance. As there are many reports of avian mortality due to collision with turbine blades, the detection and tracking of birds at turbine sites is an important issue. In this work, three different background subtraction techniques are first applied to detect moving objects. Otsu thresholding...
This paper proposes a robust detection method for circular objects in noisy and inhomogeneous contrast image. This method detects circular objects not by the difference in image intensities between the object interior and its surrounding, but by the separability and uniformity of the image intensity distributions as calculated by Bhattacharyya Coefficient. The proposed method can detect obscure and...
This paper investigates target detection problem in wireless sensor networks. Sensors carry out sensing operations and make consensus decisions about the presence or absence of a target or event. Most of previous studies for target detection either assume an unrealistic disk model for making detection decision or provide complicated numerical methods to evaluate detection performance. This paper develops...
The integration of object motion information to pixel-wise foreground segmentation is investigated for moving object detection applications. It is achieved by using a motion feedback mask as a basis to adapt parameter of background subtraction based algorithm. This binary mask indicates the possible location of foreground pixel via forwarding the previously detected object location and size. All pixels...
It is difficult to detect a stationary object in practice, especially in an unknown indoor environment, because t (a) there is no distinct speed difference between the targets and the background; (b) responses of the targets are contaminated by the dense unknown clutter; (c) a priori knowledge of the background is not always available. In the paper, a scheme is designed to enhance the signal by a...
A simple and fast algorithm for tracking multiple targets in real-time traffic scene is presented. The connected domains of moving objects, which are segmented out by the adaptive background subtraction algorithm, are obtained by morphological operation and resolution reduction. Then the track-association algorithm is applied to track the targets. The experimental results show that the proposed method...
This paper describes a novel approach for fast detecting small maritime objects in infrared (IR) images. It is based on the local minimum patterns (LMP), which are theoretically the approximations of some stationary wavelet transforms (SWT). Using LMP to estimate the background with a single image, we obtain an object-aware saliency map by background subtraction. Regions of potential objects are then...
For the inherent problem of the moving object segmentation based on the background subtraction criteria, the present paper proposes a novel shadow elimination algorithm based on HSV color space and the higher order statistics. The proposed algorithm can distinguish the changes occurring from background disturbing effects such as noise, shadows and illumination changes. It includes two stages: pre-detection...
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