Large scale performance measurement of content-based automated image-orientation detection

? With the proliferation of digital cameras and self-publishing of photos, automatic detection of image orientation will become an important part of photo management systems. In this paper, we perform a large scale empirical test to determine whether the common techniques to automatically determine a photo's orientation are robust enough to handle the breadth of real-world images. We use a wide variety of features and color-spaces to address this problem. We use test photos gathered from the web and photo collections, including photos that are in color and black and white, realistic and , and outdoor and indoor. Results show that current methods give satisfactory results on only a small subset of these images.

• Type: Conference
• Year: 2005
• Where: ICIP
• Authors: Shumeet Baluja, Henry A. Rowley
• Keywords: ICIP 2005, Image Processing, Scale Performance Measurement