Feature vector of binary image using Freeman Chain Code (FCC) representation based on structural classifier
Aini Najwa Azmi, Dewi Nasien · 2014
This paper presents a recognition system for English Handwritten that utilized Freeman Chain Code (FCC) as data representation. There are 544 features were extracted from character images that used six techniques to extract the features. Before extracting the features, thinning algorithm was applied to the original image to produce a Thinned Binary Image (TBI). A feed forward back propagation neural network was used as classification. National Institute of Standards and Technology (NIST) database are used in the experiment. The accuracy yielded from the system is 87.34%.