For a binary image containing only curves (and lines) in a background infested by binary noises, (e.g., salt-and-pepper noise,) a very efficient way to extract the image data, and to save them in a very compact file f...
详细信息
ISBN:
(纸本)0819456489
For a binary image containing only curves (and lines) in a background infested by binary noises, (e.g., salt-and-pepper noise,) a very efficient way to extract the image data, and to save them in a very compact file for an accurate and complete image recall later, is very attractive to many image processing and pattern recognition systems. This paper reports the data-extraction method we developed recently for inputting a binary image to a special neural-network pattern recognition system, the noniterative, real-time learning system. We use an adaptive/tracking window to track the direction of a continuous curve in the binary image, and record the xycoordinates of all points on this curve until the window hits an end point, or a branch point, or the original starting point. By scanning this tracking window across the whole image frame, we can then segment the original binary image into many single curves. The xy's of points on each curve can then be analyzed by a curve fitting process, and the analytic data can be stored very compactly in an analog data file. This data file can be recalled very efficiently to reconstruct the original binary image, or can be used directly for inputting to a special neural network and for carrying out an extremely fast pattern learning process. This paper reports the image-processing steps, the programming algorithm, and the experimental results on this novel image extraction technique. It will be verified in each experiment by reconstructing the original image from the compactly extracted analog data file.
The recent advance and diffusion of airborne and satellite SAR systems makes the use of multitemporal SAR images of practical interest for monitoring and control applications, especially when aiming at the identificat...
详细信息
ISBN:
(纸本)0819429597
The recent advance and diffusion of airborne and satellite SAR systems makes the use of multitemporal SAR images of practical interest for monitoring and control applications, especially when aiming at the identification of moving objects. Change detection is a powerful technique, which allows the detection of slowly moving targets. This is obtained by subtracting on a pixel-by-pixel basis the intensity of two SAR images collected at different times and comparing the absolute value of the difference to a detection threshold. Under ideal conditions, the fixed background is totally correlated and cancels out completely. On the contrary, a slowly moving target changes its position in the two images and is not cancelled. Therefore only its echo crosses the threshold. In practice, a number of factors cause the deviation from the ideal conditions; among the others the temporal decorrelation of the scene due to the internal clutter motion and the presence of misregistration and miscalibration errors. The prediction of change detection performance is essential to the design of SAR based systems for the moving target detection and should take into account all of the possible mismatch causes. In the present paper we aim at a complete mathematical characterization of the performance of change detection under non-ideal conditions. Specifically, Section 2 introduces the change detection technique and discusses some of the possible deviations from the ideal conditions. The analytical derivations are presented in Section 3, together with the discussion of the achieved results. To validate the theory, the obtained performance prediction is compared to the results obtained with real SAR images in Section 4.
The ultimate goal of this paper is to track two closely spaced and unresolved targets using monopulse radar measurements, the quality of such tracking being a determinant of successful detection of target spawn. It ex...
详细信息
ISBN:
(纸本)0819459186
The ultimate goal of this paper is to track two closely spaced and unresolved targets using monopulse radar measurements, the quality of such tracking being a determinant of successful detection of target spawn. It explores statistical estimation techniques based on the maximum likelihood criterion and Gibbs sampling, and addresses concerns about the accuracy of the measurements delivered thereby. In particular, the Gibbs approach can deliver joint measurements (and the associated covariances) from both targets, and it is therefore natural to consider a joint filter. The ideas are compared, and amongst the various strategies discussed, a particle filter that operates directly on the monopulse measurements is especially promising.
In this paper, we propose a multi-agent system which uses swarming techniques to perform high accuracy Automatic Target Recognition (ATR) in a distributed manner. The proposed system can co-operatively share the infor...
详细信息
ISBN:
(纸本)9780819471598
In this paper, we propose a multi-agent system which uses swarming techniques to perform high accuracy Automatic Target Recognition (ATR) in a distributed manner. The proposed system can co-operatively share the information from low-resolution images of different looks and use this information to perform high accuracy ATR. An advanced, multiple-agent Unmanned Aerial Vehicle (UAV) systems-based approach is proposed which integrates the processing capabilities, combines detection reporting with live video exchange, and swarm behavior modalities that dramatically surpass individual sensor system performance levels. We employ real-time block-based motion analysis and compensation scheme for efficient estimation and correction of camera jitter, global motion of the camera/scene and the effects of atmospheric turbulence. Our optimized Partition Weighted Sum (PWS) approach requires only bitshifts and additions, yet achieves a stunning 16X pixel resolution enhancement, which is moreover parallizable. We develop advanced, adaptive particle-filtering based algorithms to robustly track multiple mobile targets by adaptively changing the appearance model of the selected targets. The collaborative ATR system utilizes the homographies between the sensors induced by the ground plane to overlap the local observation with the received images from other UAVs. The motion of the UAVs distorts estimated homography frame to frame. A robust dynamic homography estimation algorithm is proposed to address this, by using the homography decomposition and the ground plane surface estimation.
The Civil Air Patrol (CAP) is procuring Airborne Real-time Cueing Hyperspectral Enhanced Reconnaissance (ARCHER) systems to increase their search-and-rescue mission capability. These systems are being installed on a f...
详细信息
ISBN:
(纸本)0819457914
The Civil Air Patrol (CAP) is procuring Airborne Real-time Cueing Hyperspectral Enhanced Reconnaissance (ARCHER) systems to increase their search-and-rescue mission capability. These systems are being installed on a fleet of Gippsland GA-8 aircraft, and will position CAP to gain real-world mission experience with the application of hyperspectral sensor and processing technology to search and rescue. The ARCHER system design, data processing, and operational concept leverage several years of investment in hyperspectral technology research and airborne system demonstration programs by the Naval Research Laboratory (NRL) and Air Force Research Laboratory (AFRL). Each ARCHER system consists of a NovaSol-designed, pushbroom, visible/near-infrared (VNIR) hyperspectral imaging (HSI) sensor, a co-boresighted visible panchromatic high-resolution imaging (HRI) sensor, and a CMIGITS-III GPS/INS unit in an integrated sensor assembly mounted inside the GA8 cabin. ARCHER incorporates an on-board data processing system developed by Space Computer Corporation (SCC) to perform numerous real-time processing functions including data acquisition and recording, raw data correction, target detection, cueing and chipping, precision image geo-registration, and display and dissemination of image products and target cue information. A ground processing station is provided for post-flight data playback and analysis. This paper describes the requirements and architecture of the ARCHER system, with emphasis on data processor design, components, software, interfaces, and displays. Key sensor performance characteristics and real-time data processing features are discussed. The use of the system for detecting and geo-locating ground targets in real-time is demonstrated using test data collected in Southern California in the fall of 2004.
This paper presents a brief overview of our research in the development of an OCR system for recognition of machine-printed texts in languages that use the Arabic alphabet. The cursive nature of machine-printed Arabic...
详细信息
ISBN:
(纸本)0819413909
This paper presents a brief overview of our research in the development of an OCR system for recognition of machine-printed texts in languages that use the Arabic alphabet. The cursive nature of machine-printed Arabic makes the segmentation of words into letters a challenging problem. In our approach, through a novel preliminary segmentation technique, a word is broken into pieces where each piece may not represent a valid letter in general. Neural networks trained on a training sample set of about 500 Arabic text images are used for recognition of these pieces. The rules governing the alphabet and character-level contextual information are used for recombining these pieces into valid letters. Higher-level contextual analysis schemes including the use of an Arabic lexicon and n-grams is also under development and are expected to improve the word recognition accuracy. The segmentation, recognition, and contextual analysis processes are closely integrated using a feedback scheme. The details of preparation of the training set and some recent results on training of the networks will be presented.
Minimizing visible distortion in a quantized color image is context-dependent. Our feedback- based strategy for color image quantization looks at the quantized image as well as the original. This comparison yields use...
详细信息
ISBN:
(纸本)0819414778
Minimizing visible distortion in a quantized color image is context-dependent. Our feedback- based strategy for color image quantization looks at the quantized image as well as the original. This comparison yields useful information to guide the embedded quantization algorithm to devote, during re-quantization of the original image, more resources to areas where the most offensive distortion occurred. Our current implementation of this new strategy uses an edge detector in a scaled RGB space to reveal the location and severeness of false contours, which appear in the quantized image but not in the original. The result of this false- contour detection step is used to identify uniformly colored regions in the quantized image that are along side of significant false contours. These regions correspond directly to areas in the original image that need to be better preserved during re-quantization. A well-known divisive method and our own agglomerative method are adapted separately as the embedded quantization algorithm to demonstrate the applicability and effectiveness of this feedback-based approach.
The theory of correlation filters does not make any assumptions about the sensor or image format. Thus the same class of algorithms is readily applicable to multiple sensor environments such as IR, SAR, LADAR, or CCD ...
详细信息
ISBN:
(纸本)081942921X
The theory of correlation filters does not make any assumptions about the sensor or image format. Thus the same class of algorithms is readily applicable to multiple sensor environments such as IR, SAR, LADAR, or CCD (visual). The advantage is that the same theory is valid for multiple sensor applications, the processing steps are common (and code) are re-usable in different sensor platforms, and the algorithms are rapidly re-trainable. The paper points out the key benefits resulting from the general formulation and solution resulting from the correlation approach to ATR.
A methodology capable of quantitatively assessing the quality of hyperspectral data has become increasingly desirable as hyperspectral remote sensing technology migrates into operational systems. The quality of spectr...
详细信息
ISBN:
(纸本)0819457914
A methodology capable of quantitatively assessing the quality of hyperspectral data has become increasingly desirable as hyperspectral remote sensing technology migrates into operational systems. The quality of spectral data depends on many factors including collection parameters charactering the sensor and the scene, and the desired spectral products. Therefore, there is a recognized urgent need to understand the phenomenology associated with the collection parameters and how they relate to the quality of the information extracted from the spectral data for different applications. If such relationships can be established, data collection requirements and tasking strategies can then be formulated for these applications. A spectral quality equation with an excellent least-squares fit was established for object/anomaly detection in an earlier work [1]. This paper describes a spectral quality equation established for material identification. This spectral quality equation relates the collection parameters (i.e. spatial resolution, spectral resolution, signal-to-noise ratio, and scene complexity) to the probability of correct identification (Pi) of materials at a given probability of false alarms (Pfa).
Multi-frame correlation filters have been recently reported in the literature for the detection of moving objects. Introduced by Kerekes and Kumar [5], this technique uses a motion model to accumulate evidence over ti...
详细信息
ISBN:
(纸本)9780819486233
Multi-frame correlation filters have been recently reported in the literature for the detection of moving objects. Introduced by Kerekes and Kumar [5], this technique uses a motion model to accumulate evidence over time in a Bayesian framework to improve the receiver operating characteristic (ROC) curve. In this paper, we generalize the approach to not only detect objects, but also their activities by using separate motion models to represent each activity. We also discuss results of preliminary simulations using publicly released aerial data set to illustrate the concept.
暂无评论