Automatic foreground detection based on KDE and binary classification

Rice Classification and Quality Detection Based on Sparse Coding Technique

Classification of various rice types and determination of its quality is a major issue in the scientific and commercial fields associated with modern agriculture. In recent years, various image processing techniques are used to identify different types of agricultural products. There are also various color and texture-based features in order to achieve the desired results in this area. In this ...

A Foreground Detection System for Automatic Surveillance

Automated surveillance has long been an application goal of computer vision. An integral part of such surveillance systems is concerned with accurately segmenting foreground objects from the static background in the videos. In this thesis we introduce a novel system for background subtraction, which takes a different approach than the conventional background subtraction systems. We make the ass...

Automatic Pavement Crack Detection Based on Aerial Imagery

Road health information is an important indicator for assessing the status of the road in management systems. Identifying the abandonment of surfaces is an important process in maintaining roads and traffic safety, which is traditionally conducted on the basis of field surveys. Today, remote sensing methods, especially photogrammetric imaging, are presented. In this article, based on by UAVs im...

The Duckling Problem and Foreground Detection and Classification of Objects

Automatic Foreground Extraction Based on Difference of Gaussian

A novel algorithm for automatic foreground extraction based on difference of Gaussian (DoG) is presented. In our algorithm, DoG is employed to find the candidate keypoints of an input image in different color layers. Then, a keypoints filter algorithm is proposed to get the keypoints by removing the pseudo-keypoints and rebuilding the important keypoints. Finally, Normalized cut (Ncut) is used ...