Comparison of image retargeting algorithms with seam carving method

The rise of social media has made sharing photos and pictures more important than ever, both for personal and marketing purposes. This situation also caused the problem of converting the photos taken with the camera in a square format, where the width is higher than the height. To address this need, a recent study explored the use of the Seam Carving method to convert images to a square format while preserving their essential parts. The study compared two algorithms, Greedy and Dijkstra, in terms of processing time and consistency using a supervised image. The consistency comparison was carried out on five images, three of which were obtained from NRID, and two were created for the study. The five images were used to calculate the average consistency of the Dijkstra algorithm. In addition, 23 more images from NRID were used to compute the average consistency of the Greedy algorithm, resulting in a total of 28 images used in the analysis. The results showed that the Greedy algorithm had an average consistency that was 6.55% higher than the Dijkstra algorithm based on the five images. Furthermore, the Dijkstra algorithm took an average of 2,347% longer to process than the Greedy algorithm. The implications of these findings are significant for social media users and marketers alike. The Greedy algorithm can help maintain the essential elements of an image while making it suitable for different social media platforms. The study also highlights the importance of considering processing time when choosing an algorithm to use. Overall, this research demonstrates the potential of the Seam Carving method and provides valuable insights into the choice of algorithm for image manipulation.