The objective of this paper was to present a newly-developed approach through MATLAB-based Fourier analysis on X-ray CT images for more directly, accurately, and efficiently characterizing the morphological features of aggregates. This newly-developed approach consisted of two parts: a small library of aggregate images from X-ray CT scanning and a MATLAB program for processing those X-ray images. One key output of the MATLAB-based imaging process was the Fourier functions, which represented the surface morphological features of aggregate particles. The Fourier radial gradient transform (FRGT) was developed based on the existing concept of radial gradient transform (RGT) and employed for analyzing the main features of those Fourier functions. Through analyzing the FRGT data of various aggregate particles, a new method was developed to characterize aggregate shape, angularity, and texture. Instead of using ellipses, polygons that were determined through vertices of angularities were used to represent mineral aggregate shapes. The angularities of aggregate surfaces were determined with the newly-developed MATLAB program through analyzing the FRGT data. After the angularities and shapes were determined, the surface textures were characterized through the newly developed texture indices namely TAD (texture abundant degree) and TRD (texture roughness Degree). Based on the research findings, the following two conclusions were made: (1) the newly developed method had a highly accuracy and efficiency; (2) through FRGT, aggregate shape, angularity, and texture could be accurately calculated and evaluated in a new manner. Since the main focus of this paper was to develop and introduce the newly-developed approach, the detailed analysis and comprehensive validation of this new method will be presented in the future publications.