Seam-Carving is widely used for content-aware image resizing. To cope with the digital image forgery caused by Seam-Carving, a new detecting algorithm based on Benford’s law is presented. The algorithm utilize the probabilities of the first digits of quantized DCT coefficients from individual AC modes to detect Seam-Carving images. The experimental result shows that the performance of proposed ...

In this paper we discuss a visual interface for presenting large images on small screen devices. We use the seam carving algorithm as an example technique to improve the readability of images, experimenting with it in various ways. We explain the results of a pilot study where we examined the use of seam carving algorithms on a small screen, making comparisons with simple other image processing...

bstract. We present the development of an objective evaluation ethod based on the integration of X-illumination, morphological ractal analysis and Bayes classifier that aims at characterizing the eam-puckering appearance. The experimental results in our reearch demonstrate that a highly significant correlation coefficient an be achieved between the estimated grades and the technicianenerated gr...

An extension of 2D Seam Carving [Avidan and Shamir, 2007] is presented, which allows for automatic resizing the duration of a video without interfering with the velocities of the objects in the scene. We identify a set of pixels across different video frames to be either removed or duplicated in a seamless manner by analyzing 3D space-time sheets in the videos. Results are presented on several ...

When a video is displayed on a smaller screen than originally intended, some of the information in the video is necessarily lost. In this paper, we introduce Video Retargeting that adapts video to better suit the target display, minimizing the important information lost. We can remove uninteresting part from video like image with some important modifications to retarget it using seam carving. I...

In this paper, we present a novel technique for seam carving of stereoscopic video. It removes seams of pixels in areas that are most likely not noticed by the viewer. When applying seam carving to stereoscopic video rather than monoscopic still images, new challenges arise. The detected seams must be consistent between the left and the right view, so that no depth information is destroyed. Whe...

BACKGROUND A new image-resizing method using seam carving and a Saliency Strength Map (SSM) is proposed to preserve important contents, such as white blood cells included in blood cell images. METHODS To apply seam carving to cell images, a SSM is initially generated using a visual attention model and the structural properties of white blood cells are then used to create an energy map for sea...

Traditional video codecs like H.264/AVC encode video sequences to minimize the Mean Squared Error (MSE) at a given bitrate. Seam carving is a content-aware resizing method. In this paper, we propose a semantic video compression scheme based on seam carving. Its principle is to suppress non salient parts of the video by seam carving. The reduced sequence is then encoded with H.264/AVC and the se...

Content-aware image retargeting has attracted substantial research interests in the related research community. However, so far there is still no method can preserve important image contents and structure well without introducing deformation. To address this problem, we propose a Saliency & Structure Preserving Multi-operator (SSPM) method. SSPM classifies images into three categories utilizing...

Abstract Word clouds are proliferating on the Internet and have received much attention in visual analytics. Although word clouds can help users understand the major content of a collection of documents quickly, their ability to visually compare documents is limited. This paper introduces a new method to create semantic-preserving word clouds by leveraging tailored seam carving, a well-establis...