Semantic Evaluation and Efficiency Comparison of the Edge Pixel Neighboring Histogram in Image retrieval

A novel approach in image retrieval based on middlelevel features, instead of low-level features, is applied in trademark matching problem. The approach is developed utilizing edge pixel neighboring histograms for capturing the overall image structure. The closeness of the method to human perceptual judgment is evaluated by a subjective test along with the efficiency in comparison with four other methods known from the literature. The query set and the image database used in the tests are taken from the MPEG-7 dataset and the experimental results show a significant supremacy in semantic compatibility over the histogram of edge angles, MPEG-7’s edge histogram descriptor (EHD), and the invariant moments method. The proposed method is more efficient than the correlation method which is closer to human perception.