The first part of this paper has been devoted to the presentation of a sequential edge detection algorithm, the local detector of which uses sequential estimators of change in mean grey level. A detailed study of some...
详细信息
The first part of this paper has been devoted to the presentation of a sequential edge detection algorithm, the local detector of which uses sequential estimators of change in mean grey level. A detailed study of some sequential detectors of change in mean is presented in this second part; this study includes some comparisons issued from simulations and new theoretical results concerning the best of them.
This paper presents a new key frame extraction algorithm as well as a novel video-indexing scheme for a fast content-based browsing and retrieval in a video database. We first extract key frames by matching AHIM (Accu...
详细信息
This paper presents a new key frame extraction algorithm as well as a novel video-indexing scheme for a fast content-based browsing and retrieval in a video database. We first extract key frames by matching AHIM (Accumulated Histogram Intersection Measure) of DC image sequence constructed from the MPEG video sequence. Then we use the region segmentation-based projective histogram and its moments as database indices for video retrieval.
A sequential algorithm for edge detection using a line-byline detector of edge elements connected to a recursive edge-following scheme is presented. On each line, edge elements are detected by means of a filtering ope...
详细信息
A sequential algorithm for edge detection using a line-byline detector of edge elements connected to a recursive edge-following scheme is presented. On each line, edge elements are detected by means of a filtering operation in order to follow the slow variations of the gray level and some sequential and recursive estimators for locating jumps in this level. The edge-following problem is solved by a Kalman filter, the state model corresponding to a noisy straight line. In this first part, the complete edge detection algorithm is presented after a brief survey of edge detection methods available in the literature. Two main examples of applications are given: detection of white and black targets in the landscape in order to perform automatic driving of vehicles and detection of blood vessels in stereographic images of the brain. In the second part, a detailed study of the sequential estimators for change in mean, which are used in the line-by-line detection, will be found.
The paper investigates how to optimize the performances of unsupervised log-ratio based change detection algorithms for two-date 1-look amplitude SAR images. The usual approach of pre-processing the SAR images at diff...
详细信息
ISBN:
(纸本)9781538633274
The paper investigates how to optimize the performances of unsupervised log-ratio based change detection algorithms for two-date 1-look amplitude SAR images. The usual approach of pre-processing the SAR images at different dates with state-of-the-art despeckling filters is critically discussed. Those adaptive filters are very efficient, also for the challenging case of 1-look images, for speckle reduction of single-date image data and then for providing reliable classification, detection, or parameter estimation results. However, they are not able to ease the discrimination of statistical from structural changes in 1-look SAR images for which reliable point-target detection is nearly impractical. A simple, yet very effective, multiscale method for changedetection and automatic change mapping is proposed and tested on simulated 1-look SAR images. The adopted preprocessing is based on guided image filtering with different window sizes. It improves the detection of changed regions without introducing any geometrical constraint and significantly reduces the false alarm rate. Experimental tests on simulated SAR images and Spotlight COSMO-SkyMed images demonstrate the advantages of the proposed algorithm.
This work proposes a changedetection algorithm based on aerial images from an UAV (Unmanned Aerial Vehicle) for infrastructure rooftop monitoring. Taking pixel-wise differences simply between different temporal aeria...
详细信息
ISBN:
(纸本)9781665482530
This work proposes a changedetection algorithm based on aerial images from an UAV (Unmanned Aerial Vehicle) for infrastructure rooftop monitoring. Taking pixel-wise differences simply between different temporal aerial images for the same scene may cause many false positives because of (a) the residual misalignments even after an image alignment preprocess;and (b) shadow and lightness differences in the images. To address such inherent characteristics of UAV images that are unfavourable in image comparing, we propose to use (a) a colour distance metric based on a weighted LAB space, which can not only mitigate the shadow effects but also enable users to be flexibly involved in detecting specific-coloured objects;(b) a Gaussian-blur filtering to emphasize major changes, while neutralising subtle changes;and (c) long-edge removal and local refinement process to reduce major false positives caused by the residual misalignments. We also conduct a mock-up experiment at a real infrastructure plant to evaluate the proposed method in terms of detecting smoke, liquid leakage, and cracking ducts, which are major phonomena of industrial malfunctions and accidents. The results show that the algorithm is able to spot the smoke and liquid leakage. On the contrary, detecting cracks is found to be not straightforward as they are viewed relatively small to be detected at the drone-filming height. We also discuss how to overcome this limitation and suggest potential approaches to improve the proposed algorithm further.
The problem of detecting a change in the distribution of a statistically periodic process is investigated. The problem is posed in the framework of independent and periodically identically distributed (i.p.i.d.) proce...
详细信息
ISBN:
(纸本)9781538682098
The problem of detecting a change in the distribution of a statistically periodic process is investigated. The problem is posed in the framework of independent and periodically identically distributed (i.p.i.d.) processes, a recently introduced class of processes to model statistically periodic data. An algorithm is proposed that is shown to be robust against an uncertainty in the post-change law. The motivation for the problem comes from event detection problems in traffic data, social network data, electrocardiogram data, and neural data, where periodic statistical behavior has been observed.
Online changedetection has many applications, ranging from finance and manufacturing, to security and computer vision. Designing a change detector for use in a given domain can be very time consuming, and model-based...
详细信息
ISBN:
(纸本)9781538634288
Online changedetection has many applications, ranging from finance and manufacturing, to security and computer vision. Designing a change detector for use in a given domain can be very time consuming, and model-based algorithms often require knowledge of the underlying stochastic model. To address these issues, in this work we explore a supervised learning approach to a change detector. We implement a gradient based procedure to find the optimal parameters for a change detector. We demonstrate the methodology on both synthetic and real world data for classifying 3D laser range image data in real-time.
The paper proposes a novel change-detection algorithm for automated videosurveillance applications. The algorithm is based on the idea of incorporating into the background model a set of simple low-level features capa...
详细信息
ISBN:
(纸本)0769519717
The paper proposes a novel change-detection algorithm for automated videosurveillance applications. The algorithm is based on the idea of incorporating into the background model a set of simple low-level features capable of capturing effectively "structural" (i.e. robust with respect to illumination variations) information. Thanks to this approach, and unlike most conventional change-detectionalgorithms, the proposed algorithm is capable of handling correctly still and slow objects as well as of working properly throughout very long time spans. Moreover the algorithm can naturally interact with the higher-level processing modules found in advanced video-based surveillance systems in order to allow for flexible and intelligent background maintenance.
We propose a method for detecting structural changes in a city using images captured from vehicular mounted cameras over traversals at two different times. We first generate 3D point clouds for each traversal from the...
详细信息
ISBN:
(纸本)9781728190778
We propose a method for detecting structural changes in a city using images captured from vehicular mounted cameras over traversals at two different times. We first generate 3D point clouds for each traversal from the images and approximate GNSS/INS readings using Structure-from-Motion (SfM). A direct comparison of the two point clouds for changedetection is not ideal due to inaccurate geo-location information and possible drifts in the SfM. To circumvent this problem, we propose a deep learning-based non-rigid registration on the point clouds which allows us to compare the point clouds for structural changedetection in the scene. Furthermore, we introduce a dual thresholding check and post-processing step to enhance the robustness of our method. We collect two datasets for the evaluation of our approach. Experiments show that our method is able to detect scene changes effectively, even in the presence of viewpoint and illumination differences.
This paper focuses on the application of a semi-automatic unsupervised changedetection algorithm called Cross Correlation Analysis (CCA) to the detection of (semi-) natural grasslands changes at Very High Resolution ...
详细信息
ISBN:
(纸本)9781479979295
This paper focuses on the application of a semi-automatic unsupervised changedetection algorithm called Cross Correlation Analysis (CCA) to the detection of (semi-) natural grasslands changes at Very High Resolution (VHR). A reference validated Land Cover/ Land Use map at time T1 and only one satellite image at time T2, with T2>T1, are required to detect changes occurred at T2 in the selected target class. This approach offers the possibility to reduce the costs of changedetection when the acquisition of multi-seasonal VHR images at time T2 for supervised changedetection is too expensive or when no archive VHR image is available in the past for unsupervised comparison between T1 and T2 images. A summer Worldview-2 image for a Natura 2000 test site was considered and the results appear encouraging.
暂无评论