![]() Moreover, the algorithm has proven to be effective in automatically computing the crack lengths and widths. Results demonstrate that cracks on asphalt pavement can be detected using the proposed computer vision algorithm. A MATLAB code was developed to automate the crack detection of the captured asphalt images. To achieve this, thirteen (13) asphalt images were collected in the close-range photogrammetric survey using a ProCam-Manual Control Camera installed in Iphone 6s. This paper seeks to address this weakness by integrating photogrammetry and computer vision in detecting cracks on asphalt pavements. In Malawi, pavement inspectors employ the manual crack detection approach, a method which is subjective, inconsistent, and tedious. Manual crack detection relies on the expertise and experience of specialist. Technological advances in digital cameras has enhanced photogrammetry such that high resolution images can now be collected. ![]() ![]() Crack detection equipment integrated with software have been developed to automate pavement distress detection. Pavement condition is assessed using both automated and manual methods. Cracks on the asphalt pavements are a forewarning of degradation of the structure which calls for a maintenance decision. ![]()
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