Abstract: Cracks are an important indicator of the safety status of infrastructures. Detection of cracks on civil structure is a vital task for maintaining the structural health and reliability of buildings. The proposed system has the ability to i) identify crack, ii) report the type, iii) estimate the length and width of the crack, iv) also estimate the depth of crack in pillars by 3D approach . This method presents a novel automated crack detection algorithm using particle filter. Cracks can be classified in accordance with their geometrical form as vertical, horizontal, diagonal and complex. The proposed approach eliminates the complex cracks geometry because it is very rare in structures. However, with this proposed method, we can measure 94% of all cracks. This system eliminates the need for manually tuning threshold parameters. In this paper, the system based on machine vision concepts has been developed with the goal to automate the process of crack geometry measurement. A single camera installed in a truck or even in a robot is used to take sequence of images is processed and the crack dimensions are estimated.

Keywords: Image analysis, machine vision, particle filter, crack depth, volume rendering.