This paper proposes a method to evaluate hierarchical image segmentation procedures, in order to enable comparisons between different hierarchical algorithms and of these with other (non-hierarchical) segmentation tec...
详细信息
ISBN:
(纸本)9783319405964;9783319405957
This paper proposes a method to evaluate hierarchical image segmentation procedures, in order to enable comparisons between different hierarchical algorithms and of these with other (non-hierarchical) segmentation techniques (as well as with edge detectors) to be made. The proposed method builds up on the edge-based segmentation evaluation approach by considering a set of reference human segmentations as a sample drawn from the population of different levels of detail that may be used in segmenting an image. Our main point is that, since a hierarchical sequence of segmentations approximates such population, those segmentations in the sequence that best capture each human segmentation level of detail should provide the basis for the evaluation of the hierarchical sequence as a whole. A small computational experiment is carried out to show the feasibility of our approach.
Automatic Vehicle License Plate Detection System (AVLPDS) is the extraction of vehicle license plate information from an image. Besides the safety aspects this system is used in many applications, viz. electronic paym...
详细信息
ISBN:
(纸本)9781509020287
Automatic Vehicle License Plate Detection System (AVLPDS) is the extraction of vehicle license plate information from an image. Besides the safety aspects this system is used in many applications, viz. electronic payment systems, freeway, arterial monitoring systems for traffic surveillance etc. The purpose of this paper is to present the FPGA algorithmic model of most efficient algorithm among three algorithms: Edge-based, Connected-Component based and Histogram based. Each approach is analyzed on the basis of precision and recall rates to determine the success of each approach. After comparison, we can say Histogram based approach has an advantage of being simple and thus faster. Therefore, in this paper, we have used Histogram based Edge processing approach to detect the license plate and presented the FPGA implementation of AVLPDS for the same. The whole system is implemented using MATLAB Simulink and Xilinx System Generator(XSG). Use of XSG for imageprocessing effectively reduces the complexity in structural design and contributes for hardware co-simulation. The accuracy of the algorithm is checked for different sets of input images and significant performance improvement has been found, thereby performing an optimal FPGA-based hardware implementation of AVLPDS.
This paper is concerned with experimental analysis of visual inverted pendulum servoing system. Firstly, visual inverted pendulum servoing system is introduced, and three typical imageprocessingalgorithms are descri...
详细信息
ISBN:
(纸本)9789811026690;9789811026683
This paper is concerned with experimental analysis of visual inverted pendulum servoing system. Firstly, visual inverted pendulum servoing system is introduced, and three typical imageprocessingalgorithms are described. These three algorithms are then employed to process the image of inverted pendulum captured by camera. Comparative experiments are operated, and the detection precision and real time performance are analyzed. This lays a solid foundation for future control research of visual inverted pendulum servoing system.
The necessity to process interlaced images in surveillance, reconnaissance, or further computer vision areas should be a topic of the past. But, for different reasons, it is not. So, there are situations in practice, ...
详细信息
ISBN:
(纸本)9781510600690
The necessity to process interlaced images in surveillance, reconnaissance, or further computer vision areas should be a topic of the past. But, for different reasons, it is not. So, there are situations in practice, in which interlaced images have to be processed. Since a lot of algorithms strongly degrade when working with such images directly, a usual method is to double or interpolate image lines in order to discard one of the two enclosed image frames. This is efficient but leads to weak results, in which half of the original information is lost. Alternatively, a lot of valuable computation time has to be spent to solve the highly complex motion compensation task in order to improve the results significantly. In this paper, an efficient algorithm is presented to solve this dilemma. First, the algorithm solves the complex 2-D mapping problem using the best state-of-the-art optical flow method that could be found for this purpose. But, of course, for different physical reasons there are regions which cannot properly be handled by optical flow by itself. Therefore, an efficient post-processing method detects and removes remaining artifacts afterwards, which is the main contribution of this paper. This method is based on color interpolation incorporating local image structure. The presented results document the overall performance of the approach with respect to obtained image quality and calculation time. The method is easy to implement and offers a valuable pre-processing for a lot of computer vision tasks.
This article describes a new 3D RGBD image feature, referred to as iGRaND, for use in real-time systems that use these sensors for tracking, motion capture, or robotic vision applications. iGRaND features use a novel ...
详细信息
ISBN:
(纸本)9781510601086
This article describes a new 3D RGBD image feature, referred to as iGRaND, for use in real-time systems that use these sensors for tracking, motion capture, or robotic vision applications. iGRaND features use a novel local reference frame derived from the image gradient and depth normal (hence iGRaND) that is invariant to scale and viewpoint for Lambertian surfaces. Using this reference frame, Euclidean invariant feature components are computed at keypoints which fuse local geometric shape information with surface appearance information. The performance of the feature for real-time odometry is analyzed and its computational complexity and accuracy is compared with leading alternative 3D features.
Traffic congestion remains a serious problem in transportation networks. Widely used navigation systems can only react to the presence of traffic jams but not to prevent their creation. One of the possibilities to pre...
Traffic congestion remains a serious problem in transportation networks. Widely used navigation systems can only react to the presence of traffic jams but not to prevent their creation. One of the possibilities to prevent congestion is to manage road traffic within the urban area. This work considers a route reservation approach with possibility to reroute a vehicle during a journey. This approach decomposes road segments into time-spatial slots and for every vehicle it makes the slots reservation for the corresponding route. Since the travel time in real networks cannot be determined precisely and can be considered as stochastic, we propose to use a rerouting procedure to minimize the traveling time. The experiments are carried out in microscopic simulation of a real-world traffic environment in the transportation network of Samara, Russia, using multi-agent transport simulation MATSim.
Modern demands for railway track measurements require high accuracy ( about 2-5 mm) of rails placement along the track to ensure smooth, safe and fast transportation. As a mean for railways geometry measurements we su...
详细信息
ISBN:
(纸本)9781510601413
Modern demands for railway track measurements require high accuracy ( about 2-5 mm) of rails placement along the track to ensure smooth, safe and fast transportation. As a mean for railways geometry measurements we suggest a stereoscopic system which measures 3D position of fiducial marks arranged along the track by imageprocessingalgorithms. The system accuracy was verified during laboratory tests by comparison with precise laser tracker indications. The accuracy of +/- 1.5 mm within a measurement volume 150x400x5000 mm was achieved during the tests. This confirmed that the stereoscopic system demonstrates good measurement accuracy and can be potentially used as fully automated mean for railway track inspection.
Orthogonal Frequency Division Multiplexing (OFDM) which is widely used transmission technique for all 4G communication systems faces a major issue of Peak to average power ratio (PAPR). Partial Transmit Sequence (PTS)...
详细信息
ISBN:
(纸本)9781467391979
Orthogonal Frequency Division Multiplexing (OFDM) which is widely used transmission technique for all 4G communication systems faces a major issue of Peak to average power ratio (PAPR). Partial Transmit Sequence (PTS) is the most preferred technique for the reduction of PAPR. But it involves complex searching algorithms for finding the most optimal combinations of OFDM signals. Increased complexity with any increase in the number of sub-blocks is a major drawback of PTS. In this paper, Iterative-Grouping and image-PTS (IGI-PTS) technique is proposed which mainly focuses on reducing the computational complexity involved in search of optimal phase factors. It is combination of two basic grouping and imaging techniques and further using iterations to simplify the searching process when the numbers of sub-blocks are in significantly high.
Recently, Physically Unclonable Functions (PUFs) received considerable attention in order to developing security mechanisms for applications such as Internet of Things (IoT) by exploiting the natural randomness in dev...
详细信息
ISBN:
(纸本)9781509054442
Recently, Physically Unclonable Functions (PUFs) received considerable attention in order to developing security mechanisms for applications such as Internet of Things (IoT) by exploiting the natural randomness in device-specific characteristics. This approach complements and improves the conventional security algorithms that are vulnerable to security attacks due to recent advances in computational technology and fully automated hacking systems. In this project, we propose a new authentication mechanism based on a specific implementation of PUF using metallic dendrites. Dendrites are nanomaterial devices that contain unique, complex and unclonable patterns (similar to human DNAs). We propose a method to process dendrite images. The proposed framework comprises several steps including denoising, skeletonizing, pruning and feature points extraction. The feature points are represented in terms of a tree-based weighted algorithm that converts the authentication problem to a graph matching problem. The test object is compared against a database of valid patterns using a novel algorithm to perform user identification and authentication. The proposed method demonstrates a high level of accuracy and a low computational complexity that grows linearly with the number of extracted points and database size. It also significantly reduces the required in-network storage capacity and communication rates to maintain database of users in large-scale networks.
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 it...
详细信息
ISBN:
(纸本)9781509010721
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. We also describe methods for adding realistic variation to TIP images in order to robustify Machine Learning (ML) based algorithms trained on TIP. These variations are derived from cargo X-ray image formation, and include: (i) translations;(ii) magnification;(iii) rotations;(iv) noise;(v) illumination;(vi) volume and density;and (vii) obscuration. These methods are particularly relevant for representation learning, since it allows the system to learn features that are invariant to these variations. The framework also allows efficient addition of new or emerging threats to a detection system, which is important if time is critical. We have applied the framework to training ML-based cargo algorithms for (i) detection of loads (empty verification), (ii) detection of concealed cars (ii) detection of Small Metallic Threats (SMTs). TIP also enables algorithm testing under controlled conditions, allowing one to gain a deeper understanding of performance. Whilst we have focused on robustifying ML-based threat detectors, our TIP method can also be used to train and robustify human threat detectors as is done in cabin baggage screening.
暂无评论