40124869
Image Pattern Recognition Based on Examples - A Combined Statistical and Structural-Syntactic Approach
An application of combined statistical and structural-syntactic approach in Chinese character recognition is presented. The algorithm adopts a structural representation for Chinese characters, but in the classification and training process, the structural matching and parameter adjustment is conducted in a statistical way. Different from the conventional structural approaches, in this system, only a few predefined "knowledge" is required. In most cases, knowledge acquisition is simplified to "memorization" of examples, and the parameters for classification can be refined using statistical training. In this way it avoids the main difficulties inherent in the implementation of classification systems based on structural features. Compared with conventional statistical algorithms, the algorithm is based on a structural model of image patterns, so it has approximately all the advantages of structural pattern recognition algorithms. A prototype system has been realized based on this strategy, and the effectiveness of the method is verified by the experimental results.
16214442
An adaptive algorithm for text detection from natural scenes
We present a new adaptive algorithm for automatic detection of text from a natural scene. The initial cues of text regions are first detected from the captured image/video. An adaptive color modeling and searching algorithm is then utilized near the initial text cues, to discriminate text/non-text regions. EM optimization algorithm is used for color modeling, under the constraint of text layout relations for a specific language. The proposed algorithm combines the advantages of several previous approaches for text detection, and utilizes a focus-of-attention approach for text finding. The whole algorithm is applied in a prototype system that can automatically detect and recognize sign input from a video camera, and translate the signs into English text or voice streams. We present evaluation results of our algorithm on this system.
3016958
Multiple frame motion inference using belief propagation
We present an algorithm for automatic inference of human upper body motion. A graph model is proposed for inferring human motion, and motion inference is posed as a mapping problem between state nodes in the graph model and features in image patches. Belief propagation is utilized for Bayesian inference in this graph. A multiple-frame inference model/algorithm is proposed to combine both structural and temporal constraints in human motion. We also present a method for capturing constraints of human body configuration under different view angles. The algorithm is applied in a prototype system that can automatically label upper body motion from videos, without manual initialization of body parts.
8377397
Boundary recognition in sensor networks by topological methods
Wireless sensor networks are tightly associated with the underlying environment in which the sensors are deployed. The global topology of the network is of great importance to both sensor network applications and the implementation of networking functionalities. In this paper we study the problem of topology discovery, in particular, identifying boundaries in a sensor network. Suppose a large number of sensor nodes are scattered in a geometric region, with nearby nodes communicating with each other directly. Our goal is to find the boundary nodes by using only connectivity information. We do not assume any knowledge of the node locations or inter-distances, nor do we enforce that the communication graph follows the unit disk graph model. We propose a simple, distributed algorithm that correctly detects nodes on the boundaries and connects them into meaningful boundary cycles. We obtain as a byproduct the medial axis of the sensor field, which has applications in creating virtual coordinates for routing. We show by extensive simulation that the algorithm gives good results even for networks with low density. We also prove rigorously the correctness of the algorithm for continuous geometric domains.
37200874
Some remarks on Kalman filters for the multisensor fusion
Abstract Multisensor data fusion has found widespread application in industry and commerce. The purpose of data fusion is to produce an improved model or estimate of a system from a set of independent data sources. There are various multisensor data fusion approaches, of which Kalman filtering is one of the most significant. Methods for Kalman filter based data fusion includes measurement fusion and state fusion. This paper gives first a simple a review of both measurement fusion and state fusion, and secondly proposes two new methods of state fusion based on fusion procedures at the prediction and update level, respectively, of the Kalman filter. The theoretical derivation for these algorithms are derived. To illustrate their application, a simple example is performed to evaluate the proposed methods and compare their performance with the conventional state fusion method and measurement fusion methods.
34184916
Deformable spanners and applications
For a set S of points in ℝ(d), an s-spanner is a subgraph of the complete graph with node set S such that any pair of points is connected via some path in the spanner whose total length is at most s times the Euclidean distance between the points. In this paper we propose a new sparse (1 + ε)-spanner with O(n/ε(d)) edges, where ε is a specified parameter. The key property of this spanner is that it can be efficiently maintained under dynamic insertion or deletion of points, as well as under continuous motion of the points in both the kinetic data structures setting and in the more realistic blackbox displacement model we introduce. Our deformable spanner succinctly encodes all proximity information in a deforming point cloud, giving us efficient kinetic algorithms for problems such as the closest pair, the near neighbors of all points, approximate nearest neighbor search (aka approximate Voronoi diagram), well-separated pair decompositions, and approximate k-centers.
1704202
Effective steganalysis based on statistical moments of wavelet characteristic function
In this paper, an effective steganalysis based on statistical moments of wavelet characteristic function is proposed. It decomposes the test image using two-level Haar wavelet transform into nine subbands (here the image itself is considered as the LL/sub 0/ subband). For each subband, the characteristic function is calculated. The first and second statistical moments of the characteristic functions from all the subbands are selected to form an 18-dimensional feature vector for steganalysis. The Bayes classifier is utilized in classification. All of the 1096 images from the CorelDraw image database are used in our extensive experimental work. With randomly selected 100 images for training and the remaining 996 images for testing, the proposed steganalysis system can steadily achieve a correct classification rate of 79% for the non-blind Spread Spectrum watermarking algorithm proposed by Cox et ai, 88% for the blind Spread Spectrum watermarking algorithm proposed by Piva et ai, and 91% for a generic LSB embedding method, thus indicating significant advancement in steganalysis.
11678491
X-ray computed tomography methods for in vivo evaluation of local drug release systems
Recent advances in drug delivery techniques have necessitated the development of tools for in vivo monitoring of drug distributions. Gamma emission imaging and magnetic resonance imaging suffer from problems of resolution and sensitivity, respectively. We propose that the combination of X-ray CT imaging and image analysis techniques provides an excellent method for the evaluation of the transport of platinum-containing drugs from a localized, controlled release source. We correlated local carboplatin concentration with CT intensity, producing a linear relationship with a sensitivity of 62.6 /spl mu/g/mL per Hounsfield unit. As an example application, we evaluated the differences in drug transport properties between normal and ablated rabbit liver from implanted polymer millirods. The use of three-dimensional visualization provided a method of evaluating the placement of the drug delivery device in relation to the surrounding anatomy, and registration and reformatting allowed the accurate comparison of the sequence of temporal CT volumes acquired over a period of 24 h. Taking averages over radial lines extending away from the center of the implanted millirods and integrating over clinically appropriate regions, yielded information about drug release from the millirod and transport in biological tissues. Comparing implants in normal and ablated tissues, we found that ablation prior to millirod implantation greatly decreased the loss of drug from the immediate area, resulting in a higher average dose to the surrounding tissue. This work shows that X-ray CT imaging is a useful technique for the in vivo evaluation of the pharmacokinetics of platinated agents.