Recognition of similar shapes

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To recognise patterns, correlation and deconvolution techniques are frequently used. The deconvolution yields an identification signal with maximum discrimination and extreme sensibility for small fluctuations in intensity and shape. The phase only filter has the advantage of been more easy to imple...

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Detalles Bibliográficos
Autores principales: Simon, J.M., Echarri, R.M., Kaufmann G.H.
Formato: CONF
Materias:
Fourier Optics
Pattern recognition
Fourier optics
Numerical analysis
Optical correlation
Signal processing
Autocorrelation
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_0277786X_v4419_n_p624_Simon
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
id todo:paper_0277786X_v4419_n_p624_Simon
record_format dspace
spelling todo:paper_0277786X_v4419_n_p624_Simon2023-10-03T15:16:19Z Recognition of similar shapes Simon, J.M. Echarri, R.M. Kaufmann G.H. Fourier Optics Pattern recognition Fourier optics Numerical analysis Optical correlation Signal processing Autocorrelation Pattern recognition To recognise patterns, correlation and deconvolution techniques are frequently used. The deconvolution yields an identification signal with maximum discrimination and extreme sensibility for small fluctuations in intensity and shape. The phase only filter has the advantage of been more easy to implement in laboratory and it can yield a recognition signal even when object and filter are only slightly similar. The autocorrelation exhibits the latter behaviour to a greater extent (specially when simple objects are to be recognised). In some cases what is of interest is not the equality but the similarity of shapes, e.g., when objects which appear in a fragmented way are to be recognised. In the present article a method to adjust the degree of acceptable similarity between filter and object is proposed and the object is recognised by means of a simple change in a coefficient appearing in the numerical proccessing. CONF info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_0277786X_v4419_n_p624_Simon
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic Fourier Optics
Pattern recognition
Fourier optics
Numerical analysis
Optical correlation
Signal processing
Autocorrelation
Pattern recognition
spellingShingle Fourier Optics
Pattern recognition
Fourier optics
Numerical analysis
Optical correlation
Signal processing
Autocorrelation
Pattern recognition
Simon, J.M.
Echarri, R.M.
Kaufmann G.H.
Recognition of similar shapes
topic_facet Fourier Optics
Pattern recognition
Fourier optics
Numerical analysis
Optical correlation
Signal processing
Autocorrelation
Pattern recognition
description To recognise patterns, correlation and deconvolution techniques are frequently used. The deconvolution yields an identification signal with maximum discrimination and extreme sensibility for small fluctuations in intensity and shape. The phase only filter has the advantage of been more easy to implement in laboratory and it can yield a recognition signal even when object and filter are only slightly similar. The autocorrelation exhibits the latter behaviour to a greater extent (specially when simple objects are to be recognised). In some cases what is of interest is not the equality but the similarity of shapes, e.g., when objects which appear in a fragmented way are to be recognised. In the present article a method to adjust the degree of acceptable similarity between filter and object is proposed and the object is recognised by means of a simple change in a coefficient appearing in the numerical proccessing.
format CONF
author Simon, J.M.
Echarri, R.M.
Kaufmann G.H.
author_facet Simon, J.M.
Echarri, R.M.
Kaufmann G.H.
author_sort Simon, J.M.
title Recognition of similar shapes
title_short Recognition of similar shapes
title_full Recognition of similar shapes
title_fullStr Recognition of similar shapes
title_full_unstemmed Recognition of similar shapes
title_sort recognition of similar shapes
url http://hdl.handle.net/20.500.12110/paper_0277786X_v4419_n_p624_Simon
work_keys_str_mv AT simonjm recognitionofsimilarshapes
AT echarrirm recognitionofsimilarshapes
AT kaufmanngh recognitionofsimilarshapes
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