Fractal Dimension Based on Morphological Covering for Ground Target Classification
نویسندگان
چکیده
منابع مشابه
Fractal dimension analysis for automatic morphological galaxy classification
In this report we present experimental results using Haussdorf-Besicovich fractal dimension for performing morphological galaxy classification. The fractal dimension is a topological, structural and spatial property that give us information about the space were an object lives. We have calculated the fractal dimension value of the main types of galaxies: ellipticals, spirals and irregulars; and...
متن کاملIRIS Classification based on Fractal Dimension Box Counting Method
Among many biometrics approaches, iris recognition is known for its high reliability, but as databases grow ever larger, an approach is needed that can reduce matching time. This can be easily achieved by using iris classification This paper presents fractal dimension box counting method for classifying the iris images into four categories according to texture pattern. Initially eye image is lo...
متن کاملLocal fractal dimension based approaches for colonic polyp classification
This work introduces texture analysis methods that are based on computing the local fractal dimension (LFD; or also called the local density function) and applies them for colonic polyp classification. The methods are tested on 8 HD-endoscopic image databases, where each database is acquired using different imaging modalities (Pentax's i-Scan technology combined with or without staining the muc...
متن کاملBox-covering algorithm for fractal dimension of weighted networks.
Box-covering algorithm is a widely used method to measure the fractal dimension of complex networks. Existing researches mainly deal with the fractal dimension of unweighted networks. Here, the classical box covering algorithm is modified to deal with the fractal dimension of weighted networks. Box size length is obtained by accumulating the distance between two nodes connected directly and gra...
متن کاملBox-covering algorithm for fractal dimension of complex networks.
The self-similarity of complex networks is typically investigated through computational algorithms, the primary task of which is to cover the structure with a minimal number of boxes. Here we introduce a box-covering algorithm that outperforms previous ones in most cases. For the two benchmark cases tested, namely, the E. coli and the World Wide Web (WWW) networks, our results show that the imp...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Shock and Vibration
سال: 2016
ISSN: 1070-9622,1875-9203
DOI: 10.1155/2016/4548365