Crack sealing is a maintenance technique commonly used to prevent water and debris penetration and reduce future degradation in pavement. The conventional crack sealing operations are, however, dangerous, costly and labor-intensive. Labor turnover and training are also increasing problems related to crack sealing crews. Automating crack sealing will improve productivity and quality, and offer safety benefits by getting workers off the road. The reduction in crew size and the increase in productivity of the automated sealing process will be translated directly into significant potential cost savings. The main objective of this study is to develop an automated system for sealing cracks in pavement, and to validate the developed system through field trials. A machine vision algorithm, which is composed of noise elimination, crack network mapping and modeling, and path planning, was developed to operate the proposed automated system effectively. Extension of the algorithms and tools presented in the study to other applications is also recommended for future studies.