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Image processing (IP) techniques have recently been applied in the field of asphalt materials to help identify aggregate particles and measure their geometrical information based on sectional images of the material. This study examined IP techniques to improve the accuracy of analyzing the size distribution of aggregates in an asphalt mixture, and proposed two new methods: seven-layer overlaying (SLO) and size-based multiple erosion (SBME) to solve the problem of identifying connected aggregate particles that often occurs in typical IP applications. The proposed methods were tested for their effectiveness with a typical IP method using a referenced sectional image of asphalt mixture. Both the proposed methods successfully improved the accuracy of detection (number and size distribution) of aggregate particles, but the SBME approach was superior over the SLO method.

Development of a Size-Based Multiple Erosion Technique to Estimate the Aggregate Gradation in an Asphalt Mixture