In this paper we perform a characterization of the objectionable image content (pornography and nude images) of the Chilean web (.cl domain). This characterization is based on a novel objectionable image filtering system that detects porno and nude images. In an automated process we examine all .cl websites, and download a large number of the available images. Then, we analyze the images? contents and we detect human-skin blobs. Afterwards, special features are derived from these skin blobs (size, orientation, position, solidity, eccentricity, etc.). Finally, a statistical classifier is employed for classifying the images in three classes: normal, porno and nude. In addition to these, we characterize the three classes by their faces content. We present statistics of use to anyone concerned with the objectionable image content of the web in Chile. We believe that the described methodology can be employed for carrying out similar studies in other segments of the web, and also for the automatic discovering of new pornographic sites.