On the basis of the Scale Invariant Feature Transform (SIFT) feature, we research the distance measure in the\r\nprocess of image resizing. Through extracting SIFT features from the original image and the resized one,\r\nrespectively, we match the SIFT features between two images, and calculate the distance for SIFT feature vectors to\r\nevaluate the degree of similarity between the original and the resized image. On the basis of the Euclidean\r\ndistance measure, an effective image resizing algorithm combining Seam Carving with Scaling is proposed. We first\r\nresize an image using Seam Carving, and calculate the similarity distance between the original image and its\r\nresized one. Before the salient object and content are damaged obviously, we stop Seam Carving and transfer\r\nresidual task to Scaling. Experiments show that our algorithm is able to avoid the damage and distortion of image\r\ncontent and preserve both the local structure and the global visual effect of the image graciously.
Loading....