IMPLEMENTATION OF IMAGE TEXTURE ANALYSIS USING NEIGHBORHOOD GREY TONE DIFFERENT MATRIX METHOD - JAMALUDIN, NORHIDAYAH (Universiti Teknologi PETRONAS, 2006)
Texturehas found in wide application in imageprocessing and it is commonly agreed that texture analysis plays a fundamental role in classifying objects or images. Two approaches have evolved over the years for texture analysis, which are called statistical and structural analysis. In recent studies, the texture classification and discrimination usually approached by using statistical analysis. Therefore, this project is carried out to distinguish the application of statistical analysis especially in the approach of Neighborhood Grey Tone Different Matrix (NGDTM) in image classification. This project presents the NGTDMapproach of image texture analysis by using MATLAB. Thus, three types of texture selected, which consist of thirty images respectively, are analyzed using the algorithm of first and second order statistic developed in MATLAB. First order statistic extractsthe statistical parameters from the image and second order statistic specifically NGTDM emphasizes on the intensities of neighboring pixels. The first and second order characteristics of each image are varying to each other, which are lead to the classification of texture. As a result, each of the input images is successfully classified regarding to its type of texture. Future work on image classification can be conducted for the use of application, such as medical image processing and remote sensing community.