Testing a Method for Statistical Image Classification in Image Retrieval

We continued to test our image classification methodology in the photo-annotation task of the ImageCLEF competition [Nowak et al., 2011] using a visual-only approach performing automated labeling however with little algorithmic improvement as compared to last year. Our labeling process consisted of three phases: 1) feature extraction using color and structural description; 2) classification using Linear Discriminant (LD), which provided the confidence (scalar) values; 3) postprocessing by eliminating labels (setting binary values to 0) on the testing set thereby exploiting the calculated joint-probabilities for pairs of concepts from the training set. Our conclusions remain the same as last year: our approach provides reasonable, fast image classification.