In order to reduce a dilapidation of Thai E-san heritages by directly accessing and touching, it is found that digital Library can be a solution to represent, retrieval, and study Thai E-san culture heritages. This digital library was started with organization of a heritage image collection through classification technique. Therefore, this work is motivated by two drivers. First, it aims to apply an alternative dimension of Content-based Image Retrieval (CBIR) to classify a collection of Thai E-san heritage images into two classes: the class of heritage images with human, and the class of heritage images without human (e.g. images of ancient remains and antiques). Second, it also proposes a method of CBIR to automatically classify a heritage image collection based on color features. This approach is valuable for the automatically classifying heritage images, where it is a time-consuming and labour-intensive process if it is done by manual classification. Two techniques are proposed to classify and organize the collection of Thai E-san heritage images: the Normalized R/G ratio and the Naïve Bayes Image classifier based on edge histogram. After testing, the experimental results show the average accuracy of the Normalized R/G ratio at 72.5%, and the average accuracy of the Naïve Bayes Image classifier based on edge histogram at 86%. This would demonstrate that our approach can be sufficiently reliable for approach.