Seam carving with improved edge preservation

Abstract

Figure 1. Our new algorithm compared to scaling and regular seam carving with forward energy. In this example, the width is reduced to 60% of the original size. ABSTRACTIn this paper, we propose a new method to adapt the resolution of images to the limited display resolution of mobile devices. We use the seam carving technique to identify and remove less relevant content in images. Seam carving achieves a high adaptation quality for landscape images and distortions caused by the removal of seams are very low compared to other techniques like scaling or cropping. However, if an image depicts objects with straight lines or regular patterns like buildings, the visual quality of the adapted images is much lower. Errors caused by seam carving are especially obvious if straight lines become curved or disconnected. In order to preserve straight lines, our algorithm applies line detection in addition to the normal energy function of seam carving. The energy in the local neighborhood of the intersection point of a seam and a straight line is increased to prevent other seams from removing adjacent pixels. We evaluate our improved seam carving algorithm and compare the results with regular seam carving. In case of landscape images with no straight lines, traditional seam carving and our enhanced approach lead to very similar results. However, in the case of objects with straight lines, the quality of our results is significantly better.

Salient edge and region aware image retargeting

“…Line detection is used in addition to the normal energy function of seam carving to preserve edges [9] and an improvement of this work is presented in [10]. These methods are effective in reducing distortions in line structure of an image, but line detection needs extra computation and it does no help for images not showing line-like structure.…”

Algorithms for video retargeting

“…Errors caused by seam carving are especially disturbing when the original image includes regular patterns or straight lines [34]. These lines may become curved or disconnected in the target image.…”

Panoramic Image Communication for Mobile Application using Content-Aware Image Resizing Method

“…Then we need to employ partial derivative operation on x, y direction with a smoothing filter. As can be described in the [7], the governing function is defined as the sum of the gradient in horizontal and vertical both directions: (1) where I means an image and ∂/∂x and ∂/∂y are partial derivative operations on x and y direction. In other words, Eq (1) is a measuring form for variation of the image in horizontal and vertical directions and then assigning a transformed value to each pixel.…”