Statistical Feature based Pattern Recognition and Classification using SVM Classifier
| Author(s) | : | Neeru Gupta, Manasvi Mannan |
| Institution | : | PCET, Lalru, Punjab, INDIA |
| Published In | : | Vol. 3, Issue 8 — August 2016 |
| Page No. | : | 28-31 |
| Domain | : | Engineering |
| Type | : | Research Paper |
| ISSN (Online) | : | 2348-4470 |
| ISSN (Print) | : | 2348-6406 |
The pattern recognition is an important activity when assembling a system composed of different parts likekeyboards. In that case manual inspection becomes tedious task due to bulk volume. Here comes the role of machinevision system that works on the principal of pattern recognition system. The image acquisition device captures thepatterns image and image processing algorithm prepares the image for feature extraction process. Different featuresincluding radii profile mean radius, area, perimeter and figure aspects are extracted around the statistical centre ofmass. The features are then classified using a classifier for pattern classification. A support vector machine algorithm isemployed to classify the patterns into their respective classes.
Neeru Gupta, Manasvi Mannan, “Statistical Feature based Pattern Recognition and Classification using SVM Classifier”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 3, Issue 8, pp. 28-31, August 2016.
