Recognition of architectural and electrical symbols by COSFIRE filters with inhibition

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Abstract

The automatic recognition of symbols can be used to automatically convert scanned drawings into digital representations compatible with computer aided design software. We propose a novel approach to automatically recognize architectural and electrical symbols.
The proposed method extends the existing trainable COSFIRE approach
by adding an inhibition mechanism that is inspired by shape-selective
TEO neurons in visual cortex. A COSFIRE filter with inhibition takes
as input excitatory and inhibitory responses from line and edge detectors. The type (excitatory or inhibitory) and the spatial arrangement
of low level features are determined in an automatic configuration step
that analyzes two types of prototype pattern called positive and negative.
Excitatory features are extracted from a positive pattern and inhibitory
features are extracted from one or more negative patterns. In our experiments we use four subsets of images with different noise levels from
the Graphics Recognition data set (GREC 2011) and demonstrate that
the inhibition mechanism that we introduce improves the effectiveness
of recognition substantially.
Original languageEnglish
Title of host publicationComputer Analysis of Images and Patterns
PublisherSpringer
Pages348-358
Number of pages11
Volume9257
Publication statusPublished - 2015
Event16th International Conference on Computer Analysis of Images and Patterns - Valletta, Malta
Duration: 2-Sep-20154-Sep-2015

Publication series

NameLecture Notes in Computer Science
PublisherSpringer International Publishing

Conference

Conference16th International Conference on Computer Analysis of Images and Patterns
Country/TerritoryMalta
CityValletta
Period02/09/201504/09/2015

Keywords

  • COSFIRE
  • trainable filters
  • architectural and electrical symbols
  • shape
  • inhibition
  • brain-inspired
  • visual cortex

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