Recognition of architectural and electrical symbols by COSFIRE filters with inhibition

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.