Melasma is the common hyperpigmentary skin disorder that can cause bright and dark brown macules and patches on sun-exposed areas of the skin owing to hyperactivity of epidermal melanocytes. Correspondingly, melanocyte detection and subsequent observation are principle procedures conducted by physicians. In this paper, we utilize methodology of contextual comparison based on intrinsic cell characteristics to detect epidermal melanocytes, which can provide consistent and accurate results for assisting the assessment of diagnosis. In addition, we propose the method of Computer-Aided Diagnosis (CAD) via moving window statistical analysis, which evaluate the relationship between detected melanocytes and the characteristics of the intercellular distribution in the Third Harmonic Generation (THG) image. The experimental results show the inconsistent distribution of cells around melanocytes in different disease categories, while processing of an adequate number of in vivo virtual biopsy images provides quantitative and objective bio-information.