Абстрактный

Offline Kannada Handwritten Word Recognition Using Locality Preserving Projection (LPP) for Feature Extraction

M.S. Patel, Rohith Kumar, S.C. Linga Reddy

Offline Handwritten Word Recognition (HWR) plays a major role in the field of image processing and pattern recognition. Compared to online recognition, handwritten words cannot be identified easily because of the variations in the handwriting styles, type of paper used, quality of the scanner etc. In our paper we have focused on the Kannada handwritten word recognition. Large number of characters present in the Kannada language makes it as a open problem for the researchers. Major steps in offline Kannada HWR are preprocessing, feature extraction, and classification. Locality Preserving Projections (LPP) method is used here for the feature extraction. For the classification Support Vector Machines (SVM) is used. Result is compared with the K-Means classifier. Experimental results show that SVM is better than K-Means classifier for our data set.

Отказ от ответственности: Этот реферат был переведен с помощью инструментов искусственного интеллекта и еще не прошел проверку или верификацию

Индексировано в

Академические ключи
ResearchBible
CiteFactor
Космос ЕСЛИ
РефСик
Университет Хамдарда
Всемирный каталог научных журналов
научный руководитель
Импакт-фактор Международного инновационного журнала (IIJIF)
Международный институт организованных исследований (I2OR)
Cosmos

Посмотреть больше