Statistical subpixel pattern recognition by histograms

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

A new statistical pattern recognition method has been developed for detection, recognition or measurement of patterns which are (much) smaller than the measure of the elementary pixel windows in the image screen. In this measurement the gray-level histogram of the objects examined is compared with the simulated histograms of different (in type or size) possible objects, and the recognition (of shape or measure) is taken on the basis of the comparison. This method does not need ultra-precise movement of the scanning sensors or any additional hardwares. Moreover, the examined pattern should be randomly distributed on the screen, or a random movement of camera (or target or both) is needed. Effect of noises are analyzed, and filtering processes are suggested in the histogram domain. Several examples of different shapes are presented through simulations and experiments.

Original languageEnglish
Title of host publicationConference B
Subtitle of host publicationPattern Recognition Methodology and Systems
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages705-708
Number of pages4
Volume2
ISBN (Print)0818629150
DOIs
Publication statusPublished - Jan 1 1992
Event11th IAPR International Conference on Pattern Recognition, IAPR 1992 - The Hague, Netherlands
Duration: Aug 30 1992Sep 3 1992

Other

Other11th IAPR International Conference on Pattern Recognition, IAPR 1992
CountryNetherlands
CityThe Hague
Period8/30/929/3/92

Fingerprint

Pattern recognition
Pixels
Cameras
Scanning
Hardware
Sensors
Experiments

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

Cite this

Szirányi, T. (1992). Statistical subpixel pattern recognition by histograms. In Conference B: Pattern Recognition Methodology and Systems (Vol. 2, pp. 705-708). [201874] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICPR.1992.201874

Statistical subpixel pattern recognition by histograms. / Szirányi, T.

Conference B: Pattern Recognition Methodology and Systems. Vol. 2 Institute of Electrical and Electronics Engineers Inc., 1992. p. 705-708 201874.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Szirányi, T 1992, Statistical subpixel pattern recognition by histograms. in Conference B: Pattern Recognition Methodology and Systems. vol. 2, 201874, Institute of Electrical and Electronics Engineers Inc., pp. 705-708, 11th IAPR International Conference on Pattern Recognition, IAPR 1992, The Hague, Netherlands, 8/30/92. https://doi.org/10.1109/ICPR.1992.201874
Szirányi T. Statistical subpixel pattern recognition by histograms. In Conference B: Pattern Recognition Methodology and Systems. Vol. 2. Institute of Electrical and Electronics Engineers Inc. 1992. p. 705-708. 201874 https://doi.org/10.1109/ICPR.1992.201874
Szirányi, T. / Statistical subpixel pattern recognition by histograms. Conference B: Pattern Recognition Methodology and Systems. Vol. 2 Institute of Electrical and Electronics Engineers Inc., 1992. pp. 705-708
@inproceedings{61200c41b19a4b4db66bd22e1e48c391,
title = "Statistical subpixel pattern recognition by histograms",
abstract = "A new statistical pattern recognition method has been developed for detection, recognition or measurement of patterns which are (much) smaller than the measure of the elementary pixel windows in the image screen. In this measurement the gray-level histogram of the objects examined is compared with the simulated histograms of different (in type or size) possible objects, and the recognition (of shape or measure) is taken on the basis of the comparison. This method does not need ultra-precise movement of the scanning sensors or any additional hardwares. Moreover, the examined pattern should be randomly distributed on the screen, or a random movement of camera (or target or both) is needed. Effect of noises are analyzed, and filtering processes are suggested in the histogram domain. Several examples of different shapes are presented through simulations and experiments.",
author = "T. Szir{\'a}nyi",
year = "1992",
month = "1",
day = "1",
doi = "10.1109/ICPR.1992.201874",
language = "English",
isbn = "0818629150",
volume = "2",
pages = "705--708",
booktitle = "Conference B",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - GEN

T1 - Statistical subpixel pattern recognition by histograms

AU - Szirányi, T.

PY - 1992/1/1

Y1 - 1992/1/1

N2 - A new statistical pattern recognition method has been developed for detection, recognition or measurement of patterns which are (much) smaller than the measure of the elementary pixel windows in the image screen. In this measurement the gray-level histogram of the objects examined is compared with the simulated histograms of different (in type or size) possible objects, and the recognition (of shape or measure) is taken on the basis of the comparison. This method does not need ultra-precise movement of the scanning sensors or any additional hardwares. Moreover, the examined pattern should be randomly distributed on the screen, or a random movement of camera (or target or both) is needed. Effect of noises are analyzed, and filtering processes are suggested in the histogram domain. Several examples of different shapes are presented through simulations and experiments.

AB - A new statistical pattern recognition method has been developed for detection, recognition or measurement of patterns which are (much) smaller than the measure of the elementary pixel windows in the image screen. In this measurement the gray-level histogram of the objects examined is compared with the simulated histograms of different (in type or size) possible objects, and the recognition (of shape or measure) is taken on the basis of the comparison. This method does not need ultra-precise movement of the scanning sensors or any additional hardwares. Moreover, the examined pattern should be randomly distributed on the screen, or a random movement of camera (or target or both) is needed. Effect of noises are analyzed, and filtering processes are suggested in the histogram domain. Several examples of different shapes are presented through simulations and experiments.

UR - http://www.scopus.com/inward/record.url?scp=85028856166&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85028856166&partnerID=8YFLogxK

U2 - 10.1109/ICPR.1992.201874

DO - 10.1109/ICPR.1992.201874

M3 - Conference contribution

SN - 0818629150

VL - 2

SP - 705

EP - 708

BT - Conference B

PB - Institute of Electrical and Electronics Engineers Inc.

ER -