Jumlah Transisi pada Ciri Transisi dalam Pengenalan Pola Tulisan Tangan Aksara Jawa Nglegeno dengan Multiclass Support Vector Machines
Abstract: Feature extraction
is one of the most improtant step on characters recognition system. Transition
features is one from many features used on characters recognition system. This
paper report a research on handwritten basic Jawanesse characters recognition system
to found the proper numbers of transitions used on transition features. To
recognize the characters,the Multiclass Support Vector Machines were used. The
Directed Acyclic Graph (DAG) SVM were used for multiclass classification
strategy and to map each input vector to a higher dimention space, the Gaussian
Radial Basis Function (RBF) kernel with parameter 1were used. It can be shown,
for basicJawanesse characters recognition system, the optimal numbers of
transitions used for transition features is 4 (a half of maximum numbers of
transition on all patterns).
Keywords: Handwritten
characters recognition, Jawanesecharacters, Transition Features, Multiclass
SVM, DAG SVM
Penulis: Azis Wisnu Widhi
Nugraha, Widhiatmoko Hery Purnomo
Kode Jurnal: jptindustridd120171
