Application of pattern recognition techniques to the identification of aerospace acoustic sources

A pattern recognition system was developed that successfully recognizes simulated spectra of five different types of transportation noise sources. The system generates hyperplanes during a training stage to separate the classes and correctly classify unknown patterns in classification mode. A feature selector in the system reduces a large number of features to a smaller optimal set, maximizing performance and minimizing computation

Vision Review

This report describes research done at the Artificial Intelligence Laboratory of the Massachusetts Institute of Technology. Support for the laboratory's artificial intelligence research is provided in part by the Advanced Research Projects Agency of the Department of Defense under Office of Naval Research contract N00014-75-C-0643.MIT Artificial Intelligence Laboratory Department of Defense Advanced Research Projects Agenc

Thue systems for pattern recognition

This report presents a synoptic overview of Thue Systems. Thue Systems were introduced in the early 1900s by the Norwegian mathematician and logician Axel Thue. In this report the author suggests ways in which such systems can be used in pattern recognition.peer-reviewe

Trends in Pattern Recognition and Machine Learning

This paper is tutorial in nature introducing the statistical and syntactic pattern recognition technique. The problem of pattern recognition has special reference with image analysis and some aspects of modern methods and application of the area of shape analysis and detection of objects included

A hill-sliding strategy for initialization of Gaussian clusters in the multidimensional space

A hill sliding technique was devised to extract Gaussian clusters from the multivariate probability density estimate of sample data for the first step of iterative unsupervised classification. Each cluster was assumed to posses a unimodal normal distribution. A clustering function proposed distinguished elements of a cluster under formation from the rest in the feature space. Initial clusters were extracted one by one according to the hill sliding tactics. A dimensionless cluster compactness parameter was proposed as a universal measure of cluster goodness and used satisfactorily in test runs with LANDSAT multispectral scanner data. The normalized divergence, defined by the cluster divergence divided by the entropy of the entire sample data, was utilized as a general separability measure between clusters. An overall clustering objective function was set forth in terms of cluster covariance matrices, from which the cluster compactness measure could be deduced. Minimal improvement of initial data partitioning was evaluated by this objective function in eliminating scattered sparse data points. The hill sliding clustering technique developed herein has the potential applicability to decomposition any multivariate mixture distribution into a number of unimodal distributions when an appropriate distribution function to the data set is employed

Linear, Deterministic, and Order-Invariant Initialization Methods for the K-Means Clustering Algorithm

Over the past five decades, k-means has become the clustering algorithm of choice in many application domains primarily due to its simplicity, time/space efficiency, and invariance to the ordering of the data points. Unfortunately, the algorithm's sensitivity to the initial selection of the cluster centers remains to be its most serious drawback. Numerous initialization methods have been proposed to address this drawback. Many of these methods, however, have time complexity superlinear in the number of data points, which makes them impractical for large data sets. On the other hand, linear methods are often random and/or sensitive to the ordering of the data points. These methods are generally unreliable in that the quality of their results is unpredictable. Therefore, it is common practice to perform multiple runs of such methods and take the output of the run that produces the best results. Such a practice, however, greatly increases the computational requirements of the otherwise highly efficient k-means algorithm. In this chapter, we investigate the empirical performance of six linear, deterministic (non-random), and order-invariant k-means initialization methods on a large and diverse collection of data sets from the UCI Machine Learning Repository. The results demonstrate that two relatively unknown hierarchical initialization methods due to Su and Dy outperform the remaining four methods with respect to two objective effectiveness criteria. In addition, a recent method due to Erisoglu et al. performs surprisingly poorly.Comment: 21 pages, 2 figures, 5 tables, Partitional Clustering Algorithms (Springer, 2014). arXiv admin note: substantial text overlap with arXiv:1304.7465, arXiv:1209.196

Residual acceleration data on IML-1: Development of a data reduction and dissemination plan

A residual acceleration data analysis plan is developed that will allow principal investigators of low-gravity experiments to efficiently process their experimental results in conjunction with accelerometer data. The basic approach consisted of the following program of research: (1) identification of sensitive experiments and sensitivity ranges by order of magnitude estimates, numerical modelling, and investigator input; (2) research and development towards reduction, supplementation, and dissemination of residual acceleration data; and (3) implementation of the plan on existing acceleration data bases

Automatic Car Registration Plate Recognition Using the Hough Transform

The development of automatic car registration plate recognition systems will provide greater efficiency for vehicle monitoring in automatic access control, and will avoid the need to equip vehicles with special RF tags for identification since all vehicles possess a unique registration plate. Thus this study is an attempt to introduce an automatic car registration plate recognition system based on identifying the plate characters by using the Hough transform. However, the proposed recognition system can be used in conjunction with a tag system for higher security access control. The automatic registration plate recognition could also have considerable potential in a wide range of applications especially in the identification of vehicle-based offences and with law enforcement. Recent advances in computer vision technology and the falling price of the related devices has contributed in making it practical to build an automatic, registration plate recognition systems. There have been a number of Optical Character Recognition (OCR) techniques, which have been used in the recognition of car registration plate characters. These systems include the character details matching process (Lotufo, et al. 1990), BAM (Bi-directional Associative Memories) neural network (Fahmy 1994) neural network (Tindall, 1995) and cross correlation pattern matching character matching techniques (Cornelli, et al. 1995). All of these systems recognized the characters by matching the full image of every character with a character\u27s template database which requires considerable processing time and large memory for the database. The purpose of this study is to explore the potential for using Hough transform (Hough 1962) in vehicle registration plate recognition. The OCR technique used in this project is unlike the other systems where the character recognition was based on matching the character\u27s full image; However the OCR technique in this system used Hough transform to identify the characters, where the recognition of a character is based on matching its identification array to the database. To validate the research, a car registration plate recognition system was developed to locate the registration plate from the full image of a vehicle and then extrar.t the plate characters by using image processing techniques. A Hough transform algorithm was applied to every character within the registration plate image to produce an identification array for these characters, and the plate characters were recognized by matching their identification array to the database. The system has been applied to a number of video recorded car images to recognize their registration plates. The rate of correctly recognized characters was 82.7% of the extracted characters, but improvement can be granted by using a faster digital camera and taking some precautions in the registration plate frames. However, the research indicated that the optical character recognition technique used in the study is an efficient and simple algorithm to identify characters, without requiring a relatively large processing memory

A methodology for the characterization of land use using medium-resolution spatial images

Introducción: La caracterización de los usos del suelo representa uno de los insumos indispensables para el manejo de los recursos naturales a diferentes escalas. Objetivo: Desarrollar una metodología para caracterizar el uso del suelo en la cuenca superior del arroyo del Azul (Buenos Aires, Argentina), a través de la fusión de imágenes satelitales de media resolución espacial. Materiales y métodos: Se utilizó una serie temporal de 23 imágenes del índice de vegetación de diferencia normalizada (NDVI, por sus siglas en inglés) del satélite MODIS-Terra (producto MOD13Q1) para el periodo mayo 2015 - mayo 2016. Además, se emplearon imágenes Landsat 8 para discriminar algunas categorías difíciles de clasificar con NDVI-MODIS. El mapa final de coberturas se validó considerando puntos de verificación independientes al proceso de clasificación; su precisión se evaluó a través del estadístico Kappa. Resultados y discusión: La serie temporal de NDVI permitió reconocer los patrones fenológicos de las coberturas y usos del suelo de mayor representatividad en la región. Se discriminaron siete coberturas; los usos agrícolas representaron 81.5 % de la superficie, siendo el sistema de doble cultivo trigo-soya (soja en Argentina) el predominante (39.4 %). La precisión global del mapa final fue alta (88.9 %, coeficiente Kappa = 0.86). Conclusión: La metodología empleada tiene la ventaja de ser rápida y replicable, para caracterizar los usos del suelo de una región determinada y evaluar sus cambios potenciales a lo largo del tiempo.Introduction: The characterization of land uses represents one of the essential inputs for the management of natural resources at different scales. Objective: To develop a methodology to characterize land use in the upper creek basin from the Azul stream (Buenos Aires, Argentina), through the fusion of satellite images with a medium spatial resolution. Materials and methods: A time-series of 23 images was used from the Normalized Difference Vegetation Index (NDVI) of the MODIS-Terra satellite (product MOD13Q1) for the period May 2015 - May 2016. Landsat 8 images were used to discriminate some categories difficult to classify with NDVI-MODIS. The final cover map was validated regarding verification points independent to the classification process; its accuracy was evaluated by means of the Kappa statistic. Results and discussion: The NDVI time series allowed to recognize the phenological patterns of the covers and land use of greater representativeness in the region. Seven land cover were discriminated; the agricultural uses represented 81.5 % of the surface, double-crop wheat-soya (soybean in Argentina) system predominated (39.4 %). The overall accuracy of the final map was high (88.9 %, Kappa coefficient = 0.86). Conclusion: The methodology used has the advantage of being quick and replicable, to characterize the land uses of a given region and to evaluate its potential changes over time.Fil: Guevara Ochoa, Cristian. Universidad Nacional del Centro de la Provincia de Buenos Aires. Rectorado. Instituto de Hidrología de Llanuras - Sede Azul. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Instituto de Hidrología de Llanuras - Sede Azul; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Lara, Bruno Daniel. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Agronomía. Departamento Ciencias Básicas Agronómicas y Biológicas. Laboratorio de Investigación y Servicios en Teledetección de Azul; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Vives, Luis Sebastián. Universidad Nacional del Centro de la Provincia de Buenos Aires. Rectorado. Instituto de Hidrología de Llanuras - Sede Azul. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Instituto de Hidrología de Llanuras - Sede Azul; ArgentinaFil: Zimmermann, Erik Daniel. Universidad Nacional de Rosario. Facultad de Ciencias Exactas Ingeniería y Agrimensura. Centro Universidad Rosario de Investigaciones Hidroambientales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Gandini, Marcelo Luciano. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Agronomía. Departamento Ciencias Básicas Agronómicas y Biológicas. Laboratorio de Investigación y Servicios en Teledetección de Azul; Argentin

Satellite on-board processing for earth resources data

Results of a survey of earth resources user applications and their data requirements, earth resources multispectral scanner sensor technology, and preprocessing algorithms for correcting the sensor outputs and for data bulk reduction are presented along with a candidate data format. Computational requirements required to implement the data analysis algorithms are included along with a review of computer architectures and organizations. Computer architectures capable of handling the algorithm computational requirements are suggested and the environmental effects of an on-board processor discussed. By relating performance parameters to the system requirements of each of the user requirements the feasibility of on-board processing is determined for each user. A tradeoff analysis is performed to determine the sensitivity of results to each of the system parameters. Significant results and conclusions are discussed, and recommendations are presented