Roads can experience a variety of distresses due to the combined effects of heavy traffic, weather, the materials used to build them, the underlying soil, and the way they were constructed. Some of these distresses that occur in flexible pavements are longitudinal and transverse cracks, potholes, patching, and depressions. The severity of these distresses increases over time, which has a negative impact on ride quality. To maintain the pavement in a safe and serviceable condition, early detection and measurement of the severity of distresses are required. Image processing techniques are a modern method for detecting and measuring pavement distresses using digital images and image processing software. Traditional methods for measuring distress are laborious, slow, and risky for the measurers. In contrast, image processing techniques are simple, safe, and quick to complete. This research paper performs image processing methods and measurements using two image processing programs, one for detection and the other for measuring pavement distresses. A comparison of image measurements with traditional measurements showed that the two methods are highly correlated, with image measurements being very close to those obtained using the traditional method. The results of the study showed that the measurements of the length, width, and area of road distresses obtained using image processing techniques were similar to those obtained using the traditional method, with high coefficients of determination R² of 0.9999, 0.9257, and 0.9451, respectively.