|Judul||:||Optimization of Pattern Recognition of Hijaiyah Letters using Normalized Cross Correlation Techniques|
The development of analysis in digital image increasingly developed with various methods, one of which is in the recognition of letter patterns. Each letter written using handwriting must have different writing patterns, such as thickness and shape of the letter pattern. In this research will be done the pattern recognition of hijaiyah letters of handwriting by applying the Normalized Cross Correlation (NCC) technique. NCC is a technique used to match of two images. Before the NCC process, it should be done the preprocessing using convolution and without convolution using binary image. The convolution technique used was the Sobel and prewitt edge detection with the aimed to get the edge of an object and compared the number of matching letters between using edge detection and without edge detection. The test was done by using different sized image of 32x32 pixel, 64x64 pixel and then match it against a similar sample data, a different sample data, a different objects font sample data and a different sample data of original image size. The results show that the matching of the letter pattern depends on the size of the image that is more matching to the image of 32x32 pixel. Binary image had better matching numbers than the convolution techniques. While in convolution techniques, prewitt edge detection had the higher accuracy and matching results compared to the image using sobel edge detection.
|Tahun||:||2019||Media Publikasi||:||Jurnal Internasional|
|Kategori||:||Jurnal||No/Vol/Tahun||:||2S7 / 8 / 2019|
|PTN/S||:||Universitas Pakuan||Program Studi||:||MANAJEMEN INFORMATIKA (D3)|