Key Point Detection in Images Based on Triangle Distribution of Directed Complex Network

Abstract

Key point detection is still a challenging issue in pattern recognition. With the recent developments on complex network theory, pattern recognition techniques based on graphs have improved considerably. Key point detection can be approached by community identification in directed complex network because image is related with network model. This paper presents a complex network approach for key point detection in video monitoring image, which is both accurate and fast. We evaluate our method for square and subway station video monitoring images. Results show that our algorithm can outperform other traditional method both in accuracy and processing times.

Modelling Selected Parameters of Power Grid Network in the South-Eastern Part of Poland: The Case Study

“…The theory of complex systems and its applications to modeling network behavior and parameters has brought new methodology and interesting concepts in many areas of science [1]. There are many examples of possible applications [2][3][4][5][6]. Power systems are exposed to a wide range of security threats, including cyber-attacks, failures of its different devices and nodes, weather extreme conditions, terrorist attacks, etc.…”