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Land cover change assessment is one of the main applications of remote sensed data. Change in forest cover have widespread effects on the provision of ecosystem services, and provide important feedbacks to climate change and biodiversity. Moreover, it will be extremely critical if the accuracy of image interpretation can be improved for better understanding the change of forest. Parametric methods...
Content based retrieval and recognition of objects represented in images is a challenging problem making it an active research topic. Shape analysis is one of the main approaches to the problem. In this paper we propose the use of a reduced set of features to describe 2D shapes in images. The design of the proposed technique aims to result in a short and simple to extract shape description. We conducted...
A novel classification method of video shot genre based on data-mining has been proposed. Shot boundary detection and key frames extraction are firstly performed. Then, some visual features such as color and motion are extracted for the key frame and shots. Furthermore, decision tree is applied to discover the rules between these features and shots genres from numerous training data. These rules are...
In this article, we present a contribution to the violent Web images classification. This subject is deeply important as it has a potential use for many applications such as violent Web sites filtering. We propose to combine the techniques of image analysis and data-mining to relate low level characteristics extracted from the image's colors to a higher characteristic of violence which could be contained...
This research is focused on using digital image processing and machine learning techniques to classify electrofused magnesia for industry automation. We generate the data from different images by using a modern digital image process. This research proposes a new method to construct the digital image database. The proposed new method is based on simple histogram mode and intensity deviation. A group...
Selecting suitable features is very crucial for achieving successful classification of land cover types. This paper presents a comparative study of three typical feature selection methods for the task of regional land cover classification using MODIS data. Comparison results have shown that Branch and Bound is the best for land cover classification with MODIS data, while ReliefF and mRMR achieve nearly...
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