Seam carving is a popular method of resizing an image while maintaining important content by adding or removing seams. The key to this approach is the importance map, distinguishing seams of the least visual significance. Nevertheless, traditional approaches struggle to preserve local and global image characteristics, causing visible artifacts that can significantly diminish visual fidelity. This study presents a new importance map combining Bubble Entropy, a Euclidean distance saliency map, and Haar wavelets for edge detection. Bubble Entropy is excellent at finding regularity and structural continuity across pixel neighborhoods, tracing significant seams. The saliency map's perceptually uniform property enhances color variation assessment, improving the detection of salient regions and textures. Additionally, Haar wavelet transforms enhance edge detection by maintaining structural transitions while resizing. By calculating the combined importance map, the proposed approach settles at the optimal balance between local and global characteristics of an image. The proposed algorithm outperforms previous seam carving algorithms in terms of perceptual quality metrics: LPIPS, MSSIM, HyperIQA and TOPIQ with the RetargetMe dataset. Execution time was also significantly reduced using the Numba package. Experimental results show image content preservation while improving visual quality and presenting a stronger approach for content-aware image resizing.
seam carving, entropy, bubble entropy, saliency map, haar, wavelet filter
Eliza Joyce B. Lim. Corresponding author. 4th Year Bachelor of Science in Computer Science Student at Pamantasan ng Lungsod ng Maynila. Email: elizalim036@gmail.com
Louweesiana M. Buscas. 4th Year Bachelor of Science in Computer Science Student at Pamantasan ng Lungsod ng Maynila.
Vivien A. Agustin. Master in Information Technology and CISTM Professor at Pamantasan ng Lungsod ng Maynila.
Khatalyn E. Mata. Doctor in Information Technology and CISTM Dean at Pamantasan ng Lungsod ng Maynila.
"Eliza Joyce B. Lim handled algorithm development and result analysis. Louweesiana M. Buscas performed comprehensive literature research and contributed to the manuscript writing. Vivien A. Agustin provided supervision and critical revisions throughout the research process. Dr. Khatalyn E. Mata provided supervisory input, reviewed and refined the paper, and approved its final version for submission."
No potential conflict of interest was reported by the author(s).
This research is supported by the Department of Science and Technology (DOST) through the DOST-SEI Undergraduate Scholarship.
The author declares the use of Artificial Intelligence (AI) in writing this paper. In particular, the author used QuillBot in paraphrasing ideas and ChatGPT in summarizing key points. The author takes full responsibility in ensuring proper review and editing of contents generated using AI.
This paper is presented in the 2nd International Student Research Congress (ISRC) 2025
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Cite this article:
Lim, E.J.B., Buscas, L.M., Agustin, V.A. & Mata, K.E. (2025). Enhancement of seam carving algorithm for optimized content-aware image resizing application. International Student Research Review, 2(1), 74-90. https://doi.org/10.53378/isrr.165
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