26302852
Some New Results on Isotonic Array Grammars
16442037
Handwritten Bank Check Recognition Of Courtesy Amounts
In spite of rapid evolution of electronic techniques, a number of large-scale applications continue to rely on the use of paper as the dominant medium. This is especially true for processing of bank checks. This paper examines the issue of reading the numerical amount field. In the case of checks, the segmentation of unconstrained strings into individual digits is a challenging task because of connected and overlapping digits, broken digits, and digits that are physically connected to pieces of strokes from neighboring digits. The proposed architecture involves four stages: segmentation of the string into individual digits, normalization, recognition of each character using a neural network classifier, and syntactic verification. Overall, this paper highlights the importance of employing a hybrid architecture that incorporates multiple approaches to provide high recognition rates.
31996759
Analysis and Design of Parallel Thinning Algorithms - A Generic Approach
In this paper, a generic approach for the analysis and design of parallel thinning algorithms is presented. The procedures for designing 4-subcycle/iteration, 2-subcycle/iteration, and 1-subcycle/iteration thinning algorithms are developed. The experimental results show that these thinning algorithms designed by proposed approach preserve image connectivity, produce thinner results, and obtain faster speed than many existing key thinning algorithms. As an example, a 1-subcycle/iteration algorithm and its experimental results were illustrated, which is in general about two times faster than others in the literature.
207116582
A Thinning Algorithm Based on the Force Between Charged Particles
A new thinning algorithm based on the well known concept of the force of attraction or repulsion between charged particles is presented. This algorithm generates connected skeletons which preserve the shape and end-points of the original patterns. Its performance is experimentally compared with four other known algorithms published in the literature. For the sake of comparison, a reasoned set of test data is introduced. The results of our comparison reveal that the proposed CPM (Charge Particle Method) algorithm is almost as fast as the fastest of those compared. For thin images obtainable from low resolution scanners or coarse scanned images, the CPM algorithm is the fastest.
2857808
A knowledge-based segmentation algorithm for enhanced recognition of handwritten courtesy amounts
Abstract A knowledge-based segmentation algorithm to enhance recognition of courtesy amounts on bank checks is proposed in this paper. This algorithm uses multiple contextual cues to enhance segmentation and recognition. The system described extracts context from the handwritten numerals and uses a syntax parser based on a deterministic finite automaton to provide adequate feedback to enhance recognition. Further feedback is provided by a simple legal amount decoder that determines word count and recognizes several key words (e.g. thousand and hundred). This provides an additional semantic constraint on the dollar section. The segmentation analysis module presented is capable of handling a number of commonly used styles for courtesy amount representation. Both handwritten and machine written courtesy and legal amounts were utilized to test the efficacy of the preprocessor for the check recognition system described in this paper. The substitution error was reduced by 30–40% depending on the input check mix.
38659056
Intelligent Pattern Recognition and Applications
8410122
On connectivity of reconfigurable impact networks in ageless aerospace vehicles
The research results presented in this paper were obtained as part of the joint CSIRO-NASA Ageless Aerospace Vehicle (AAV) project. We describe the underlying principles, methodology, and preliminary results of modelling and simulating a multi-cellular sensor and communication network in a dynamic decentralised setting, motivated by a self-monitoring, self-repairing AAV. Such networks are expected to detect and react to multiple impacts and damage over a wide range of impact energies. In particular, we address the problem of forming a reconfigurable network (a minimum spanning tree) connecting cells that detected non-critical impacts, in presence of connectivity disruptions caused by critical impacts. The presented algorithm is based on the ant colony metaphor and may be complemented by gradient-based techniques. In addition, we measure the robustness of impact networks and present quantitative metrics that clearly identify phase transitions in network connectivity, separating chaotic dynamics from ordered and robust patterns. © 2005 Elsevier B.V. All rights reserved.
18326845
Parallel univariate p-adic lifting on shared-memory multiprocessors
Parallelization of univariate p-aclic lifting, a procedure important in modem gcd and factorization algorithms, is presented. The strategy is to take the fastest known sequential algorithm and parallelize its key steps: lift basis, residue, correction coefficients, updating factors, cldecting true factors, and reformulation for continued lifting. Both linear and quadratic lifting are investigated. A new procedure for reformulating the lifting after finding true factors speeds up the sequential and the parallel lifting. PLIFT, a software package written in C for a 26-processor Sequent Balance, implements the parallel algorithms. Timing results are given in an appendix,
15278727
LOCI: Load Shedding through Class-Preserving Data Acquisition
An avalanche of data available in the stream form is overstretching our data analyzing ability. In this paper, we propose a novel load shedding method that enables fast and accurate stream data classification. We transform input data so that its class information concentrates on a few features, and we introduce a progressive classifier that makes prediction with partial input. We take advantage of stream data's temporal locality -for example, readings from a temperature sensor usually do not change dramatically over a short period of time -for load shedding. We first show that temporal locality of the original data is preserved by our transform, then we utilize positive and negative knowledge about the data (which is of much smaller size than the data itself) for classification. We employ both analytical and empirical analysis to demonstrate the advantage of our approach.
15398175
Hardware-based Packet Classification Made Fast and Efficient
To achieve fast packet classification, a hardware-based scheme, cross-producting recurrence (CPR), based on a formerly proposed cross-producting scheme is proposed. This scheme simplifies the classification procedure and decrease the distinct combinations of fields by hierarchically decomposing the multi-dimensional space. In the new scheme, the multi-dimensional space is endowed with a hierarchical property which self-divides into several smaller subspaces, whereas the procedure of packet classification is translated into repeatedly searching for matching subspaces. The required storage of the proposed scheme is significantly reduced since the distinct fields of subspaces is controlled by a pre-defined configuration and can be much less than that of the filters. The experimental results demonstrate the effectiveness and scalability of the proposed scheme
5826256
Confidence as Higher-Order Uncertainty
With conflicting evidence, a reasoning system derives uncertain conclusions. If the system is open to new evidence, it faces additionally a higher-order uncertainty, because the first-order uncertainty evaluations are uncertain themselves — they can be changed by future evidence. A new measurement, confidence, is introduced for this higher-order uncertainty. It is defined in terms of the amount of available evidence, and interpreted and processed as the relative stability of the first-order uncertainty evaluation. Its relation with other approaches of “reasoning with uncertainty” is also discussed.