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This project presents Field Programmable Gate Array (FPGA) based solution for an object tracking system. The tracking design was applied in FPGA as rich information of FPGA offers one of the more powerful methods in object tracking. Object tracking system has a very useful application in many real world situations which require object detection. In general, a lot of different algorithms are used in...
Advances in technology continue to make both hardware and software affordable and accessible; we have seen a rapid growth in computer vision and image processing applications. One area of interest in vision and image processing is automated identification of objects in real-time or recorded video streams and analysis of these identified objects. An important topic of research in this context is identification...
Video compression algorithms are time consuming processes. A key part of video compression algorithms which is also time consuming is motion estimation (ME) and computation of motion vectors (MVs). During this process, a series of candidate blocks should be searched to find the best motion vectors. In this paper, we propose a method for reducing the motion estimation process time. The idea of our...
In this paper we have developed a technique for low level data fusion between laser and monocular color camera using occupancy grid framework in the context of internal representation of external environment for object detection. Based on a small variant of background subtraction technique we construct an occupancy grid for camera and fuse it with the one constructed for laser to get a combined view...
Background subtraction is widely used for extracting unusual motion of object of interest in video images. In this paper, we propose a fast and flexible approach of object detection based on an adaptive background subtraction technique that also effectively eliminates shadows based on color constancy principle in RGB color space. This approach can be used for both outdoor and indoor environments....
This paper focuses on the fast and automatic detection and segmentation of unknown objects in unknown environments. Many existing object detection and segmentation methods assume prior knowledge about the object or human interference. However, an autonomous system operating in the real world will often be confronted with previously unseen objects. To solve this problem, we propose a segmentation approach...
When mosaicking two adjacent orthophotos, the transition from one orthophoto to the other is cannot be seen. The requirements of such an optimal seamline include high color similarity and high texture similarity. In this paper, a novel method integrated snakes and bresenham is presented. The calculation of photometric energy in the snake model considers not only the discrete points, but all the points...
In this paper, a target localization method based on color recognition and connected component analysis is presented. The raw image is converted to HSI color space through a lookup table, followed by a line-by-line scan to find all the connected domains. By checking the size of each domain, most pseudo targets can be omitted and, meanwhile, the target position would be calculated. Owing to the absence...
Edge detection is very important in image process. According the three standards in edge detection: optimal detection result, optimal location and low repeat response, optimal linear filter is deduced. Base on the standards, a simple BMP edge Detection algorithm is proposed, improved algorithm and color scope D algorithm are given. Experiments prove that running speed of algorithms is satisfied and...
The improved moving object detection and shadow removing algorithms for video surveillance are presented in this paper. The proposed algorithm processes two foregrounds performed by improved GMM and chromaticity-gradient background subtraction methods. The proposed algorithm improves the classic Gaussian Mixture Model to remove some unfavorable influences, such as sudden and gradual illumination changes,...
The purpose of this paper is the design of target recognition system based on machine vision. Through the needs analysis of the system, hardware platform and software platform is built on machine vision. The scheme of machine vision based on PXI bus is put forwarded. The VISION module which is the machine vision of Lab VIEW software is introduced. The target (star) of the image acquisition and target...
A moving object segmentation algorithm based on edge detection is put forward in this paper. The algorithm reconstructs background from image sequence. It uses edge detection to eliminate the disturbance of shadow, and uses Gaussian filter to eliminate noise. The background subtraction is used to extract moving object. The experimental results show that this algorithm effectually avoids the influence...
This work address the issues and difficulties related to the design of an autonomous robot capable of performing unknown objects segmentation and material classification task. One of the most challenging aspects of such a system is that the robot has to segment unknown objects from a complicated scene and in the proximity of other objects. In this paper, illuminations of different frequencies are...
Vision-based driver assistance system in complex urban area is highly demanding. The basic requirement for the system is the capacity of detecting potential obstacles. In particular, the automobile, it is more dangerous than other objects. Facing the sensitive area called as “interesting area” in front of the driver within a certain range, this paper presents an object detection method fully using...
Line detection in digital images is a fundamental aspect of many problems in computer vision. In the light of the problems, such as heavy computation and intensive memory occupation, existing in the Hough Transform, an improved fast line detection algorithm combining the time-frequency domain transform and the spatial domain transform is proposed. First, the wavelet lifting is used to extract low...
This paper presents a new approach for estimating the pose, or position and orientation, of a target object relative to a camera. The approach assumes that the object geometry is known and that identifiable feature points on the object are tracked. Using the epipolar constraint, the problems of estimating orientation and position are decoupled. The orientation estimation problem is formulated and...
The cast shadows on the background of the object or scene will definitely affect the recognition of the foreground objects. Due to this unavoidable problem, the performance of the successful object recognition, image analysis and object tracking algorithms would be degraded. An efficient shadow detection and removal algorithm is necessary to make the algorithms outperform in the analysis, recognition...
In object tracking identifying the best feature which discriminates object and background improves the performance. Most of the existing methods do not consider the suitability of such features for the tracker. Here we enhance the discriminative features which elevate the tracker performance. To accommodate object and background variations over time we dynamically update the best feature using a distance...
The detection of license plate region is the most important part of a vehicle's license plate recognition process followed by plate segmentation and optical character recognition. Edge detection is commonly used in license plate detection as a preprocessing technique. This paper compares the performance of the image enhancement filters when used in edge detection algorithms combined with connected...
Automatic Number Plate Recognition (ANPR) systems allow users to track, identify and monitor moving vehicles by automatically extracting their number plates. This paper presents an improved method to locate car plates in an ANPR system. The proposed method is based on morphological open and close operations where different Structuring Elements (SE) are used to maximally eliminate non-plate region...
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