Halftone based block truncation coding images (H-BTC) are the improved version of BTC images which can offer superior representation and enhanced image quality. The application of the H-BTC images range from image compression and retrieval, indexing, reconstruction, classification and so on. In this paper, a brief introduction to various H-BTC images is presented and their evaluation is carried out in terms of image quality and computational demand. Further, the application prospective of the H-BTC images are also provided. The developed H-BTC database comprises of 30K images comprising of the five types of H-BTC images in which three categories are constructed based on digital halftoning and two types are based on digital multitoning. The database would be very useful to carry out deep learning research and various image processing tasks. The database along with its source code will be made open source for the research and academic purpose.