Fractal dimension is an effective measure for complex objects. It is widely applied in the fields of image segmentation and shape recognition. Algorithms to estimate the fractal dimension already exist, such as the straightforward quadratic algorithm and box-counting algorithms. However, these algorithms are not space efficient. This paper contributes a very faster method to estimate the correlation fractal dimensionality of the points and also a very spaceefficient one. The proposed algorithm computes the fractal dimension in a single pass and also uses a constant amount of memory. In this work we have taken five main types of fractal and compared average fit error of the existing and the proposed algorithms. The experimental results demonstrate the effectiveness of the proposed algorithm.
