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Annotating photographs automatically with content descriptions facilitates organization, storage, and search over visual information. We present an integrated approach for scene classification that combines image-based and text-based approaches. On the text side, we use the text accompanying an image in a novel TF* IDF vector-based approach to classification. On the image side, we present a novel OF* IIF (object frequency) vector-based approach to classification. Objects are defined by clustering of segmented regions of training images. The image based OF* IIF approach is synergistic with the text based TF* IDF approach. By integrating the TF* IDF approach and the OF* IIF approach, we achieved a classification accuracy of 86%. This is an improvement of approximately 12% over existing image classifiers, an improvement of approximately 3% over the TF* IDF image classifier based on textual information, and an improvement of approximately 4% over the OF* IIF image classifier based on visual information.