This paper presents work on the development of automatic feature extraction from multispectral aerial images and lidar data based on test data from two different study areas with different characteristics. First, we filtered the lidar point clouds to generate a Digital Terrain Model (DTM) using a novel filtering technique based on a linear first-order equation which describes a tilted plane sur...

This paper describes a novel system for real-time video texture analysis. The system utilizes hardware to extract 2-order statistical features from video frames. These features are based on the Gray Level Co-occurrence Matrix (GLCM) and describe the textural content of the video frames. They can be used in a variety of video analysis and pattern recognition applications, such as remote sensing,...

ii To my family and friends iii ABSTRACT Surface textures are the most salient characteristics of an object as it encode surface details. Texture classification is the process to classify the images into different classes of textures and has been widely used in various implementations based on the textural information of the subjects, such as face detection, defects detection and rock classific...

Abstract: Classification of the cervical cell is one of the most important and crucial tasks in the medical image analysis. Due to its importance, the aim of the paper is to investigate about the classification of Cervical Cell as Normal Cell or Abnormal Cell by using individual feature extraction method and combining individual feature extraction features method with the classification techniq...

With advancement in technology, especially imaging field, digital image forgery has increased a lot nowadays. In order to counter this problem, many detection techniques have been developed from time time. For rapid and accurate of forged image, novel hybrid technique is used research work that implements Gray Level Co-occurrence Matrix (GLCM) along with Binary Robust Invariant Scalable Keypoin...

In our study we investigated the relationship between conventional morphometric indicators of nuclear size and shape (area and circularity) and the parameters of gray level co-occurrence matrix texture analysis (entropy, homogeneity, and angular second moment) in cells committed to apoptosis. A total of 432 lymphocyte nuclei images from the spleen germinal center light zones (cells in early sta...

The traditional gray level co-occurrence matrix (GLCM) is in two-dimensional form. Because hyperspectral imagery in the feature space has the characteristic of volumetric data, it has a great potential for three-dimensional texture analysis. Previous studies have successfully extended traditional 2D GLCM to a 3D form (Gray Level Co-occurrence Matrix for Volumetric Data, GLCMVD) for extracting f...