A Hybridized Feature Extraction Model for Offline Yorùbá Document Recognition
نویسندگان
چکیده
Document recognition is required to convert handwritten and text documents into digital equivalents, making them more easily accessible convenient store. This study combined feature extraction techniques for recognizing Yorùbá in an effort preserve the cultural values heritages of people. Ten were acquired from Kwara State University’s Library, ten indigenous literate writers wrote version documents. These digitized using HP Scanjet300 pre-processed. The pre-processed image served as input Local Binary Pattern, Speeded-Up-Robust-Features Histogram Gradient. extracted vectors Genetic Algorithm. reduced vector was fed Support Vector Machine. A 10-folds cross-validation used train model: LBP-GA, SURF-GA, HOG-GA, LBP-SURF-GA, HOG-SURF-GA, LBP-HOG-GA LBP-HOG-SURF-GA. LBP-HOG-SURF-GA printed gave 90.0% precision, 90.3% accuracy 15.5% FPR. Handwritten document showed 80.9% 82.6% 20.4% (FPR) CEDAR 98.0% 98.4% 2.6% MNIST 99% 99.5% accuracy, 99.0% 1.1% results hybridized extractions (LBP-HOG-SURF) demonstrated that proposed work improves significantly on various classification metrics.
منابع مشابه
Hybridized Feature Extraction and Acoustic Modelling Approach for Dysarthric Speech Recognition
Dysarthria is malfunctioning of motor speech caused by faintness in the human nervous system. It is characterized by the slurred speech along with physical impairment which restricts their communication and creates the lack of confidence and affects the lifestyle. This paper attempt to increase the efficiency of Automatic Speech Recognition (ASR) system for unimpaired speech signal. It describe...
متن کاملSupervised Feature Extraction of Face Images for Improvement of Recognition Accuracy
Dimensionality reduction methods transform or select a low dimensional feature space to efficiently represent the original high dimensional feature space of data. Feature reduction techniques are an important step in many pattern recognition problems in different fields especially in analyzing of high dimensional data. Hyperspectral images are acquired by remote sensors and human face images ar...
متن کاملOffline Kannada Handwritten Word Recognition Using Locality Preserving Projection (LPP) for Feature Extraction
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 characte...
متن کاملNeural Network Based Recognition System Integrating Feature Extraction and Classification for English Handwritten
Handwriting recognition has been one of the active and challenging research areas in the field of image processing and pattern recognition. It has numerous applications that includes, reading aid for blind, bank cheques and conversion of any hand written document into structural text form. Neural Network (NN) with its inherent learning ability offers promising solutions for handwritten characte...
متن کاملFeature Extraction for Iris Recognition
In this paper, we evaluate the performance of feature extraction methods for iris pattern classification. Generally, the identification system using iris recognition consists of the iris localization block and the iris pattern classification block. In this paper, we used the 2D bisection-based Hough transform and the radius histogram method for the iris localization and we used multilayer perce...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Asian Journal of Research in Computer Science
سال: 2023
ISSN: ['2581-8260']
DOI: https://doi.org/10.9734/ajrcos/2023/v15i4329