Automatic nudity detection strategies play an important role in solutions focusing on controlling access to inappropriate content. These strategies usually apply filter or similar approaches in order to detect nudity in digital images. In this paper we propose a strategy for nudity detection based on applying image zoning. Moreover, we perform feature extraction using color and texture information, as well as feature selection, focusing on pointing out the most relevant features. SVM is used for image classification. Experimental results demonstrate that an effective improvement in terms of accuracy is attained by using the zoning strategy. In addition, the highest classification rates are obtained by combining two color-based and two texture-based features, which shows that it is possible to reduce the number of features while keeping high classification rates.