Showing papers on "Change detection published in 1995"

Decentralized quickest change detection

Abstract: A decentralized formulation of the quickest change detection problem is studied, where the distributions of the observations at all of the sensors in the system change at the time of disruption, and the sensors communicate with a common fusion center. A Bayesian setting is considered in which a priori knowledge of the change time distribution is available. The observations are assumed to be independent from sensor to sensor, conditioned on the change hypothesis. An optimal solution to the problem is derived under a quasi-classical information structure, where each sensor retains only its messages from the past (restricted local memory), and receives feedback from the fusion center about the past messages of the other sensors (full feedback). A technique for implementation of the optimal solution is given, and the solution is extended to the situation where a priori change time distribution information is not available. The structure of the optimal solution is then used to arrive at a simple suboptimal policy that does not require any past massage information. Numerical examples are given, which illustrate that the optimal solution offers little improvement over the suboptimal one, i.e., that feedback from the fusion center cannot be exploited to improve performance.

Statistical approach to scene change detection

Abstract: One of the challenging problems in video databases is the organization of video information. Segmenting a video into a number of clips and characterizing each clip has been suggested as one mechanism for organizing video information. This approach requires a suitable method to automatically locate cut points in a video. One way of finding such cut points is to determine the boundaries between consecutive camera shots. In this paper, we address this as a statistical hypothesis testing problem and present three tests to determine cut locations. All the three tests are such that they can be applied directly to the compressed video. This avoids an unnecessary decompression-compression cycle, since it is common to store and transmit digital video in compressed form. As our experimental results indicate, the statistical approach permits accurate detection of scene changes induced through straight as well as optical cuts.

Bayesian algorithms for adaptive change detection in image sequences using Markov random fields

Abstract: In many conventional methods for change detection, the detections are carried out by comparing a test statistic, which is computed locally for each location on the image grid, with a global threshold. These ‘nonadaptive’ methods for change detection suffer from the dilemma of either causing many false alarms or missing considerable parts of non-stationary areas. This contribution presents a way out of this dilemma by viewing change detection as an inverse, ill-posed problem. As such, the problem can be solved using prior knowledge about typical properties of change masks. This reasoning leads to a Bayesian formulation of change detection, where the prior knowledge is brought to bear by appropriately specified a priori probabilities. Based on this approach, a new, adaptive algorithm for change detection is derived where the decision thresholds vary depending on context, thus improving detection performance substantially. The algorithm requires only a single raster scan per picture and increases the computional load only slightly in comparison to non-adaptive techniques.

A generalized change detection problem

Abstract: The purpose of this paper is to give a new statistical approach to the change diagnosis (detection/isolation) problem. The change detection problem has received extensive research attention; however, the change isolation problem has, for the most part, been ignored. We consider a stochastic dynamical system with abrupt changes and investigate the multiple hypotheses extension of Lorden's (1971) results. We introduce a joint criterion of optimality for the detection/isolation problem and then design a change detection/isolation algorithm. We also investigate the statistical properties of this algorithm. We prove a lower bound for the criterion in a class of sequential change detection/isolation algorithms. It is shown that the proposed algorithm is asymptotically optimal in this class. The theoretical results are applied to the case of additive changes in linear stochastic models. >

Application independent record level synchronization

Abstract: A method and an apparatus for synchronization of a first set of data with a second set of data at the record level. A memory stores a change detection mechanism for generating a Change List for the first and second sets of data. The Change List lists the changes made at the record level to the first and second sets of data. The memory also has a Synchronization mechanism for making the first set of data and the second set of data equivalent by using the information in the Change List generated by the Change Detection Mechanism. A processor runs the Change Detection mechanism and the Synchronization mechanism.

Scene change detection using quantization scale factor rate control

Abstract: A rate control algorithm for an MPEG-2 compliant encoder is described. The rate control algorithm has embodiments useful for constant bit rate and variable bit rate encoding. In particular, the invention relates to scene change detection.

Digital Change Detection Techniques in Remote Sensing

Abstract: : This report presents a review of digital change detection techniques using remotely sensed data, citing examples of their use for both environmental and military applications It also discusses some issues germane to digital change detection: image registration and rectification, thresholding, and radiometric correction

A scene change detection algorithm for MPEG compressed video sequences

Abstract: Video is an important and challenging medium and requires sophisticated indexing schemes for efficient retrieval from visual databases. An important step in video indexing is scene change detection. Recently, several scene change detection algorithms in the pixel and compressed (MPEG-2) domains have been reported in the literature. These algorithms are computationally complex and are not very robust in detecting gradual scene changes. The authors propose an efficient technique for detecting scene changes in the MPEG-2 compressed domain. The proposed algorithm has the advantage of fast scene change detection. In addition, this algorithm has the potential to detect gradual scene changes.

Optimum multisensor data fusion for image change detection

Abstract: Optimum multisensor data fusion is addressed for image change detection based on the optimum likelihood ratio test for the statistical dependence of the luminance signals in additive Gaussian noise. It is demonstrated that the information to be transmitted from the sensors to the fusion center is the maximum likelihood estimates of the correlation coefficients between pairs of consecutive image frames. Experimental results illustrate that the detection error decreases as the number of sensors and/or frames increases. >

Automatic control of camera pan, zoom and focus for improving object recognition

Abstract: In this paper we consider the use of the GETAFIX robot vision head for object recognition by automatic active panning, zooming and focussing. It is shown that given appropriate areas of interest (which may be defined by motion, change detection or colour segmentation) the sensor can be driven to isolate these regions. Subsequent processing is made more reliable in this process. The effective signal to noise ratio of the data is increased by the process and many features which were unreliably detected by passive techniques can be reliably and accurately acquired by the active approach. Experiments are demonstrated for the case of detecting cylindrical 3D objects in table-top scenes.

Scene change adaptive video encoder

Abstract: A method and apparatus for encoding a picture is provided. A plurality of input picture data are stored, and the quantity of the information of the input picture data from the plural stored picture data is evaluated for detecting a scene change. A GOP of a preset unit length, made up of a picture formed by compression by intra-frame coding and a picture formed by compression by inter-frame predictive coding, is selected based upon a scene change detection output and the input picture data is encoded in a pre-set manner in accordance with the selected GOP. By detecting a scene change and selecting the intra-frame coding as a compression method responsive to scene change detection, the compression efficiency is raised at a scene change portion of the input picture data where the correlation between previous and succeeding pictures is lowered.

Planar subarray processing for SAR imaging

Abstract: A new multiresolution SAR image formation algorithm called planar subarray processing, PSAP, is presented. The PSAP provides the capability to perform intermediate decisions using lower resolution image data to redirect the remaining processing functions. These intermediate decisions can include, target detection, change detection, super resolution, and moving target parameter estimation. The PSAP algorithm has a tree like flow structure using small cascaded FFT stages making it suitable for parallel processor implementation.

Integration of remotely-sensed raster data with a vector-based geographical information system for land-use change detection

Abstract: Methods of land-use change detection are different for raster and vector data types because of the differences in structures of the two data types. Since large amounts of land-use data (derived from existing maps and aerial photographs) are stored in vector format in a Geographical Information System (GIS), there is a need to develop a change detection algorithm for use with vector-formatted data. Since remotely-sensed images are increasingly being used to derive land-use data, it is necessary to integrate raster data with large volumes of vector data already available in a GIS. This necessitates an efficient and effective data integration technique using which raster data are to be integrated with a vector-based GIS. This paper presents a methodology of data integration of remotely-sensed raster data with vector data. A new approach is developed for land-use change detection for use with vector data in a GIS environment. The approach is based on the mathematical concepts of Sets and Groups, and ...

Optical information reproducing apparatus with a threshold level generator to eliminate DC level fluctuation

Abstract: A level sensor circuit compares a threshold level from a threshold value generator circuit with that of an input sampling signal to create a binarized pulsated signal. A change point detector circuit detects a change point of binary information indicated by the input pulsates signal or positions before and after the change point and thereby sends a change point detection signal(s) to a threshold level generator circuit. The threshold level generator circuit extracts from the sampling signals only ones at points of time when the change point detection signal is inputted from the change point detector circuit and then averages the extracted sampling signals with respect to time to generate a threshold level.

Nonparametric truncated sequential change-point detection

Abstract: New nonparametric truncated sequential changepoint detection processes are considered via a theorem of Darling and Erdös (1956). Their asymptotic and finite sample properties are examined and compared to existing procedures. They are found to stop faster than other existing procedures for relatively large changes that occur early in the sequence of observations.

Building wide area 2-D site models from high resolution fully polarimetric synthetic aperture radar images

Abstract: Wide area site models are useful for delineating regions of interest and assisting in tasks like monitoring and change detection They are also useful in registering a newly acquired image to an existing one of the same site, or to a map This paper presents a complete algorithm for building an approximate 2-D wide-area site model from high resolution, polarimetric Synthetic Aperture Radar (SAR) data A three stage algorithm-involving detection of possible targets, statistical segmentation of the data into homogeneous regions, and validation of segmentation results-is used for this task Constant False Alarm Rate (CFAR) detectors are used for target detection, while maximum likelihood labeling is used for initial segmentation Knowledge of the sensor heading and other geometric cues are used to refine the initial segmentation and to extract man-made objects like buildings, and their shadows, as well as roads, from these images

Method and device for processing moving image

Abstract: PURPOSE: To simply and surely detect a change in a video at a sufficiently high processing speed even when an exclusive device for processing the video is not prepared. CONSTITUTION: This moving image processing method is provided with a change detection step 2 for detecting a change in a video by comparing a still picture inputted from the video in a picture input step 1 with the newest changed picture obtained at the time of detecting the newest change out of video changes generated in the past, a newest change picture storing step 3 for storing the still picture to be compared at the time of detecting a change in the video as the newest changed picture. A moderate video change also can be surely detected by comparing a still picture inputted from a current video with the newest changed picture and detecting the existence of a change in the current picture.

Multichannel SAR segmentation: algorithms and applications

Abstract: Many emerging SAR applications require imagery which is multi-channel either in time, frequency, or polarization. If SAR segmentation algorithms are going to be of genuine utility they must be applicable to such datasets. Two approaches to multi-channel segmentation are considered: segmenting each channel separately and then recombining the results; and segmenting the multi-channel image as a single entity. In both cases segmentation is based on edge detection and segment growing. The utility of multi-channel segmentation for change detection, classification and analyzing the information content of multi-channel data, is discussed. A multi-temporal ERS-1 image, and a multi-polarized, multi-frequency AIRSAR image of the same agricultural scene, are used for case studies.© (1995) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Detecting change points and monitoring biomedical data

Abstract: Bayesian and likelihood approaches to on-line detecting change points in time series are discussed and applied to analyze biomedical data. Using a linear dynamic model, the Bayesian analysis outputs the conditional posterior probability of a change at time t − 1, given the data up to time t and the status of changes occurred before time t − 1. The likelihood method is based on a change-point regression model and tests whether there is no change-point.

Voice recognition device

Abstract: PROBLEM TO BE SOLVED: To reduce a processing amount and deterioration in recognition precision by investigating an hourly change of a characteristic vector, substituting a value of before one point of time for a probability calculation value when a varying amount is less, further structuring distribution of probability to a binary tree structure and performing calculation of probability based on binary tree retrieval. SOLUTION: A characteristic amount hourly change detection means 31 receives the characteristic vector at one point of time from a voice analysis means 2 to compare it with the characteristic vector before one point of time. When the hourly varying amount of the characteristic vector is less than a prescribed threshold value as the comparison result, the means 31 issues instructions to a representative distribution probability calculation means 32 so as to omit processing. Further, the number of times of probability calculation are reduced remarkably by using the representative distribution of the binary tree structure. At this time, after arriving at a final hierarchy by the binary tree retrieval, the probability calculation is performed again related to the vicinity distribution of the arrived representative distribution, and a real probability calculation value instead of an approximate value is used. Thus, the voice recognition with less processing amount becomes possible while keeping the recognition precision.

Change detection in radar images: methods and operational constraints

Abstract: In this paper the methods and operational constraints of change detection from synthetic aperture radar images are reviewed. A simulation-based environment dedicated to the evaluation of a change detection algorithm is described. Some results are presented for a linear feature detection algorithm.

Teletext data change detection and noiseless data compression

Abstract: The full channel teletext system is a high speed data broadcasting system. Pages of information are broadcast in a cyclic manner. The detection of data change in the information pages is necessary for data analysis, database update and retransmission. Lossless data compression is also necessary to enhance the data throughput in rebroadcasting and to reduce the storage requirement. Performing data change detection and data compression in real time using a software approach in a small machine is impossible for such high speed data. The authors describe the algorithms that are suitable for hardware implementation for both data change detection and noiseless data compression. They also illustrate the use of cyclic redundancy check (CRC) and dictionary based compression scheme using a hashing function to detect changes and compression respectively in the teletext pages.

Image exploitation using multi-sensor/neural network systems

Abstract: We have developed and evaluated a tool for change detection and other analysis tasks relevant to image exploitation. The tool, visGRAIL, integrates three key elements: (1) the use of multiple algorithms to extract information from images - feature extractors or {open_quotes}sensors{close_quotes}, (2) an algorithm to fuse the information - presently a neural network, and (3) empirical estimation of the fusion parameters based on a representative set of images. The system was applied to test images in the RADIUS Common Development Environment (RCDE). In a task designed to distinguish natural scenes from those containing various amounts of human-made objects and structure, the system classified correctly 95% of 350 images in a test set. This paper describes details of the feature extractors, and presents analyses of the discriminatory characteristics of the features. visGRAIL has been integrated into the RCDE.

Net comparison: an adaptive and effective method for scene change detection

Abstract: As video information proliferates managing video sources becomes increasingly im portant Automatic video partitioning is a prerequisite for organizing and indexing video sources Several methods have been introduced to tackle this problem e g pairwise and histogram comparisons Each has advantages but all are slow because they entail inspec tion of entire images Furthermore none of these methods have been able to de ne camera break and gradual transition which are basic concepts for partitioning In this paper we attempt to de ne camera break Then based on our de nition and probability analysis we propose a new video partitioning algorithm called NET Comparison NC which compares the pixels along prede ned net lines In this way only part of the image is inspected during classi cation We compare the e ectiveness of our method with other algorithms such as pairwise likelihood and histogram comparisons evaluating them on the basis of a large set of varied image sequences that include camera movements zooming moving objects deformed objects and video with degraded image quality Both gray level and HSV images were tested and our method out performed existing approaches in speed and accuracy On average our method processes images two to three time faster than the best existing approach

Device for correcting image shake

Abstract: PURPOSE:To dump a picture normally even in the case of a scene change CONSTITUTION:A video signal P1 reproduced by a video reproduction device and a correlation coefficient P3 outputted from a motion vector detection circuit 3 are inputted to a scene change detection circuit 6, in which a scene change is detected and a signal P7 representing the result of detection is outputted to a microcomputer 4 The microcomputer 4 discriminates whether or not a current field is just after a scene change based on the scene change detection signal P7 from the scene change detection circuit 6 and when the current field is just after the scene change, a weighted integral value of a motion vector P2 preserved up to now is reset and a read address P4 of the picture memory 2 is set again to be segmented from the center of the screen thereby avoiding an adverse affect on a dumping control characteristic due to a scene change

Neural network for change detection of remotely sensed imagery

Abstract: The use of a neural network for determining the change of landcover/land-use with remotely sensed data is proposed. In this study, a single image contains both spectral and temporal information is created from a multidate satellite imagery. The proposed change detection method can be divided into two main steps: training data selection and change detection. At the training step, the training set, basically consists of the classes of no-change and possible change data, is obtained from the composited image. Then the training data is used to input the neural network and obtain the network's weights. At the change detection step, the network's weights is employed to detect the change and no-change classes in the combined image. The proposed method is tested using a multidate SPOT imageries and a satisfied change pattern detection is obtained.© (1995) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Monitoring information collection system

Abstract: PURPOSE:To suppress the lowering of information collection capacity in the collection system of the monitoring information in the remote supervisory and controlling system of a polling system. CONSTITUTION:In a monitoring information change detection part 12, the sampling of the state of monitoring information is performed by a constant cycle and the change of the state is detected. In a state change information storage part 14, the state at the time of the detection of the change and the time are stored. At the time of a polling, stored data is returned. In an information collection capacity lowering detection part 15, collection capacity is always checked. When the capacity is lowered, the detection cycle of the monitoring information change detection part 12 is controlled and the storage information amount of the state change information storage part 14 is suppressed. The change of a state change detection cycle is notified to the storage part 14.

Aps channel fetching circuit

Abstract: PURPOSE:To prevent the erroneous switching operation at the time of the generation and restoration of MS-AIS in the MSP protocol processing of bidirectional line protection of a device coping with SDH. CONSTITUTION:Bytes K1 and K2 as the APS channel and a timing' signal are inputted to a change point detecting circuit 4. The change point detecting circuit detects the change of bytes K1 and K2 to generate a change point detection signal and a signal corresponding to bytes k1 and k2. An alarm detecting circuit 1 detects a signal indicating the detection of alarm included in an input byte signal to generate an alarm detection signal. A protection circuit 2 generates a protection signal in accordance with the alarm detection signal and a sampling signal. A control circuit 3 generates a control signal in accordance with the alarm detection signal and the protection signal. The change point detecting circuit 4 delays generation of the change point detection signal in accordance with the control signal.

Change detection and backscatter modeling applied to forest monitoring by SAR

Abstract: The use of the ERS-1 C band SAR for monitoring tropical forest areas is assessed, using three ERS images from the Tapajos region of Amazonia gathered in 1992. Forest areas display a very stable RCS, while non-forest areas in some cases exhibit changes which appear to be associated with soil moisture variations. Discrimination between forest and non-forest is greatest after a dry period. Because of distortions in RCS caused by topography, change detection provides a more useful discrimination approach than RCS differences on single images. A number of automatic change detection techniques are compared and their ability to classify forest and non-forest are quantitatively assessed, assuming that a forest map inferred from a 1992 Landsat TM image is correct. Block averaging followed by image ratioing provides a reasonable approach to detecting the large scale structure of the image, but simulated annealing provides improved performance at a computational cost which is becoming competitive with simpler methods. Approximately 50% of the non-forest region can be detected from the ERS-1 images. This figure may be improved by more frequent image acquisition, but there are fundamental limitations in using C band data, which would be lessened by using longer wavelengths.© (1995) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Multiaperture SAR target detection using hidden Markov models

Abstract: Multi-aperture SAR (MASAR) is an extension of conventional SAR imagery that allows anisotropic returns from man-made objects to be exploited for detection. In this paper, we propose a MASAR ATD algorithm based on hidden Markov models (HMMs). We show that this algorithm economically locates anisotropic target returns. Using simulated L-band MASAR imagery containing M35 trucks, generated by the Xpatch-es software written by Loral, we derive HMM structures that efficiently model the sub-aperture radar return trajectories for target, grass, and tree pixels. We compare HMM detection results for the simulated MASAR imagery over a 105 degree angle of integration with two alternative methods: MASAR split-aperture (SA) change detection and conventional SAR two-parameter CFAR detection. To obtain our results we group detected pixels into target-sized clusters using a clustering algorithm. The results show that HMM detection far outperforms CFAR detection while requiring 1/10th as many FLOPS per pixel. Further, HMM ATD is nearly as accurate as SA change detection while requiring less than 1/500th as many FLOPS per pixel. Finally, for a more practical 45 degree angle of integration, we show that HMM detection and SA chnage detection have equivalent performance, while HMM detection requires less than 1/185th as many FLOPS per pixel.© (1995) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.