Connected  Region  =  2

Extract  Fourier  Descriptor

Circuit Sketch Recognition !Yuchi Liu, Yao Xiao!

Department of Electrical Engineering, Stanford University

Database Preparation

Recognition Workflow

Training images

Extract Fourier descriptors

Build multiclass SVM using one-vs-rest approach

Objec:ves Approach Scale  Invariance Normalize  using    

1st  Fourier  Descriptor Rota9on  Invariance Only  Consider  Magnitude Modifica9on  tolerance Use  Coefficients  for  low  

frequencies

Binarize and filter Segmentation Recognition

Locally Adaptive Threshold; Filter noise

Find feature point; Filter spurious feature points generated by sketch.

Extract each component using feature point

Y N  

Axis  Ra:o≈1

Y N

Classify  Using  Mul:class  SVM

Future Work l  More training data for better SVM model

l  Combine other features such as image

moments as features for SVM

l  Better and faster segmentation method

References [1] G. G. Rajput, S. M. Mali. Marathi Handwritten Numeral Recognition using Fourier Descriptors and Normalized Chain Code IJCA,01 (2010). [2] D.S. Zhang, G. Lu. A Comparative Study on Shape Retrieval Using Fourier Descriptors with Different Shape Signatures International Conference on Intelligent Multimedia and Distance Education, P 1-9 (2001) [3] C. S. Fahn, J. F. Wang, J. Y. Lee. A Topology-Based Component Extractor for Understanding Electronic Circuit Diagrams. Computer Vision, Graphics, Image Processing, p 119-138 (1988)

Motivation It would be very helpful for engineers to be able to hand draw circuit sketches and process them in software to generate standardized circuit diagram. Our goal is to recognize the different electronic component using Fourier Descriptors as features for SVM for classification.

Recognized  Components