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Title: Recognition of architectural and electrical symbols by COSFIRE filters with inhibition
Authors: Guo, Jiapan
Shi, Chenyu
Azzopardi, George
Petkov, Nicolai
Keywords: Computer vision
Pattern recognition systems
Visual cortex
Issue Date: 2015
Publisher: Springer
Citation: Guo J., Shi C., Azzopardi G., & Petkov N. (2015) Recognition of Architectural and Electrical Symbols by COSFIRE Filters with Inhibition. In Azzopardi G., Petkov N. (Eds), Computer analysis of images and patterns. CAIP 2015. Lecture notes in computer science, vol 9257. Springer, Cham.
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.
Description: This is a Conference paper presented by the authors at the CAiP 2015: 16th International Conference on Computer Analysis of Images and Patterns, held in Malta from the 2 to 4 September, 2015.
ISBN: 9783319231167
Appears in Collections:Scholarly Works - FacICTAI

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