Search NASA⌕ Search

SEARCH · Search NASA

Results for “pattern recognition”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRS1974

Techniques for computer-aided analysis of ERTS-1 data, useful in geologic, forest and water resource surveys

Forestry, geology, and water resource applications were the focus of this study, which involved the use of computer-implemented pattern-recognition techniques to analyze ERTS-1 data. The results have proven the value of computer-aided analysis techniques, even in areas of mountainous terrain. Several analysis capabilities have been developed during these ERTS-1 investigations. A procedure to rotate, deskew, and geometrically scale the MSS data results in 1:24,000 scale printouts that can be directly overlayed on 7 1/2 minutes U.S.G.S. topographic maps. Several scales of computer-enhanced "false color-infrared" composites of MSS data can be obtained from a digital display unit, and emphasize the tremendous detail present in the ERTS-1 data. A grid can also be superimposed on the displayed data to aid in specifying areas of interest.

Hoffer, R. M.↗
NASA NTRS1974

Burke County wheat feasibility study

A feasibility study was conducted to determine whether wheat could be distinguished from other small grain crops in a selected spring wheat growing area in Burke County, North Dakota using a maximum likelihood classification program and ERTS 1 multispectral band scanner data. ERTS 1 data scenes were selected from passes made on June 5, 1973 and June 23, 1973. The Univac 1108 computer and the LARSYS pattern recognition software package were used in performing the classification. Results of the analysis are provided.

Kunkel, W. A.↗
NASA NTRS1974

Interpretation techniques

The image enhancement and geometric correction and registration techniques developed and/or demonstrated on ERTS data are relatively mature and greatly enhance the utility of the data for a large variety of users. Pattern recognition was improved by the use of signature extension, feature extension, and other classification techniques. Many of these techniques need to be developed and generalized to become operationally useful. Advancements in the mass precision processing of ERTS were demonstrated, providing the hope for future earth resources data to be provided in a more readily usable state. Also in evidence is an increasing and healthy interaction between the techniques developers and the user/applications investigators.

Dragg, J. L.↗
NASA NTRS1974

Remote sensing techniques for mapping range sites and estimating range yield

Image interpretation procedures for determining range yield and for extrapolating range information were investigated for an area of the Pine Ridge Indian Reservation in southwestern South Dakota. Soil and vegetative data collected in the field utilizing a grid sampling design and digital film data from color infrared film and black and white films were analyzed statistically using correlation and regression techniques. The pattern recognition techniques used were K-class, mode seeking, and thresholding. The herbage yield equation derived for the detailed test site was used to predict yield for an adjacent similar field. The herbage yield estimate for the adjacent field was 1744 lbs. of dry matter per acre and was favorably compared to the mean yield of 1830 lbs. of dry matter per acre based upon ground observations. Also an inverse relationship was observed between vegetative cover and the ratio of MSS 5 to MSS 7 of ERTS-1 imagery.

Benson, L. A.↗
NASA NTRS1973

Optical instrumentation engineering in science, technology and society; Proceedings of the Sixteenth Annual Technical Meeting, San Mateo, Calif., October 16-18, 1972

Visual tracking performance in instrumentation is discussed together with photographic pyrometry in an aeroballistic range, optical characteristics of spherical vapor bubbles in liquids, and the automatic detection and control of surface roughness by coherent diffraction patterns. Other subjects explored are related to instruments, sensors, systems, holography, and pattern recognition. Questions of data handling are also investigated, taking into account minicomputer image storage for holographic interferometry analysis, the design of a video amplifier for a 90 MHz bandwidth, and autostereoscopic screens. Individual items are announced in this issue.

Katz, Y. H.↗
NASA NTRS1973

Satellite ocean color measurements

The application of pattern recognition to ocean color data analysis is considered. Due to weight, cost, and data transmission rate limitations, any mapping type remote sensor of ocean color must necessarily collect light from the sea in a finite number of channels. The optical properties of the sea are discussed together with the remote sensing of ocean color, an optical model of natural water, the microscopic optical model, the macroscopic optical model, multiple scattering theory, measurements of subsurface oceanographic parameters, measurements of bulk absorption and scattering properties, measurements of the up- and down-welling light field, and the techniques for ocean color data analysis.

Mccluney, W. R.↗
NASA NTRS1974

Weighted adaptive algorithms for estimation of Gaussian distribution parameters

Two weighted adaptive algorithms are proposed for updating the estimates of the mean vector and the covariance matrix, respectively, in a multispectral pattern recognition system. To achieve computational efficiency, the auxiliary matrices have been utilized in the algorithm for covariance matrix updating. Enhancements in the performance accuracy of a multispectral processing system and extensions of the Gaussian maximum likelihood classification capabilities to larger scale surveys are the motivations in developing the algorithms presented herein.

Chang, C. Y.↗
NASA NTRS1975

Automated statistical analysis program (ASAP)

Pattern recognition subprogram is used to produce table which indicates sections of input data. Program then uses data to write set of Kirchhoff equations algebraically solved by Gaus reduction method.

Bavuso, S. J.↗
NASA NTRS1975

Multispectral data analysis: LARSYS III

System uses pattern recognition and interactive data handling techniques applied to remotely sensed data. Basic analysis concept consists of locating data points which are believed to be representative of classes of interest.

Landgrebe, D. A.↗
NASA NTRS1974

Evaluation of satellite remote sensing and automatic data techniques for characterization of wetlands and coastal marshlands

The author has identified the following significant results. ERTS digital data has been used to detect and measure accretion in the large estuarial system of the Atchafalaya River in southern Louisiana. Comparisons of aerial photography taken in October 1970 with a computer printout of ERTS digital data collected on October 1, 1972, show that in a delineated area of 1400 hectares (3460 acres) an accretion of land area in the amount of 112 hectares (277 acres) had occurred. Analysis of band 3 of the ERTS MSS was used to make a land-water map of the area. The accretion test area was marked on this map and the percentage of elements indicated as land was calculated. This percentage was then multiplied by the total test area to obtain the area of land on the date of the ERTS observation for comparison with the aerial photography. Significant improvement in classification accuracy of ERTS MSS data has been achieved by use of a priori probabilities of occurrence in pattern recognition programs. Two classifications were made with accuracies of 76.0% and 81.5%, respectively.

Cartmill, R. H.↗
NASA NTRS1975

A procedure for automated land use mapping using remotely sensed multispectral scanner data

A system of processing remotely sensed multispectral scanner data by computer programs to produce color-coded land use maps for large areas is described. The procedure is explained, the software and the hardware are described, and an analogous example of the procedure is presented. Detailed descriptions of the multispectral scanners currently in use are provided together with a summary of the background of current land use mapping techniques. The data analysis system used in the procedure and the pattern recognition software used are functionally described. Current efforts by the NASA Earth Resources Laboratory to evaluate operationally a less complex and less costly system are discussed in a separate section.

Whitley, S. L.↗
NASA NTRS1975

Development and testing of a portable wind sensitive directional air sampler

A portable wind sensitive directional air sampler was developed as part of an air pollution source identification system. The system is designed to identify sources of air pollution based on the directional collection of field air samples and their analysis for TSP and trace element characteristics. Sources can be identified by analyzing the data on the basis of pattern recognition concepts. The unit, designated Air Scout, receives wind direction signals from an associated wind vane. Air samples are collected on filter slides using a standard high volume air sampler drawing air through a porting arrangement which tracks the wind direction and permits collection of discrete samples. A preset timer controls the length of time each filter is in the sampling position. At the conclusion of the sampling period a new filter is automatically moved into sampling position displacing the previous filter to a storage compartment. Thus the Air Scout may be set up at a field location, loaded with up to 12 filter slides, and left to acquire air samples automatically, according to the wind, at any timer interval desired from 1 to 30 hours.

Deyo, J.↗
NASA NTRS1975

On the cost of approximating and recognizing a noise perturbed straight line or a quadratic curve segment in the plane

Approximation of noisy data in the plane by straight lines or elliptic or single-branch hyperbolic curve segments arises in pattern recognition, data compaction, and other problems. The efficient search for and approximation of data by such curves were examined. Recursive least-squares linear curve-fitting was used, and ellipses and hyperbolas are parameterized as quadratic functions in x and y. The error minimized by the algorithm is interpreted, and central processing unit (CPU) times for estimating parameters for fitting straight lines and quadratic curves were determined and compared. CPU time for data search was also determined for the case of straight line fitting. Quadratic curve fitting is shown to require about six times as much CPU time as does straight line fitting, and curves relating CPU time and fitting error were determined for straight line fitting. Results are derived on early sequential determination of whether or not the underlying curve is a straight line.

Cooper, D. B.↗
NASA NTRS1974

An introduction to quantitative remote sensing

The quantitative approach to remote sensing is discussed along with the analysis of remote sensing data. Emphasis is placed on the application of pattern recognition in numerically oriented remote sensing systems. A common background and orientation for users of the LARS computer software system is provided.

Lindenlaub, J. C.↗
NASA NTRS1975

A counter example in linear feature selection theory

The linear feature selection problem in multi-class pattern recognition is described as that of linearly transforming statistical information from n-dimensional (real Euclidean) space into k-dimensional space, while requiring that average interclass divergence in the transformed space decrease as little as possible. Divergence is the expected interclass divergence derived from Hajek two-class divergence; it is known that there always exists a k x n matrix B such that the transformation determined by B maximizes the divergence in k-dimensional space. It is known that, if Q is any k x k invertible matrix, and B is as defined above, then QB again maximizes the divergence in k-space. It is shown that the converse of this result is false: two matrices exist, B sub 1 and B sub 2, each of which maximizes transformed divergence, which are not related in the fashion B sub 2 = QB sub 1 for any k x k matrix Q.

Brown, D. R.↗
NASA NTRS1975

The decision tree approach to classification

A class of multistage decision tree classifiers is proposed and studied relative to the classification of multispectral remotely sensed data. The decision tree classifiers are shown to have the potential for improving both the classification accuracy and the computation efficiency. Dimensionality in pattern recognition is discussed and two theorems on the lower bound of logic computation for multiclass classification are derived. The automatic or optimization approach is emphasized. Experimental results on real data are reported, which clearly demonstrate the usefulness of decision tree classifiers.

Wu, C.↗
NASA NTRS1975

Bringing remote sensing technology to the user community

The procedures and services available for educating and training potential users of remote sensing technology are discussed along with approaches for achieving an in-house capability for the analysis of remotely sensed data using numerical techniques based on pattern recognition principles. Cost estimates are provided where appropriate.

Lindenlaub, J. C.↗