Enhancement of seam carving algorithm for optimized content-aware image resizing application
Eliza Joyce B. Lim, Louweesiana M. Buscas, Vivien A. Agustin & Khatalyn E. Mata
Abstract
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.
Keywords
seam carving, entropy, bubble entropy, saliency map, haar, wavelet filter
Author information & Contribution
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."
Disclosure statement
No potential conflict of interest was reported by the author(s).
Funding
This research is supported by the Department of Science and Technology (DOST) through the DOST-SEI Undergraduate Scholarship.
AI Declaration
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.
Notes
This paper is presented in the 2nd International Student Research Congress (ISRC) 2025
Acknowledgement
References
Achanta, R., & Susstrunk, S. (2009). Saliency detection for content-aware image resizing. Sixteenth IEEE International Conference on Image Processing (ICIP). https://doi.org/10.1109/ICIP.2009.5413815
Avidan, S., & Shamir, A. (2007). Seam carving for content-aware image resizing. In ACM SIGGRAPH 2007 Papers (SIGGRAPH ’07). Association for Computing Machinery, New York, NY, USA, 10–es. https://doi.org/10.1145/1275808.1276390
Avidan, S., & Shamir, A. (2009). Seam carving for media retargeting. Communications of the ACM, 52(1), 77–85. https://doi.org/10.1145/1435417.1435437
Brock, J., Ding, C., Xu, X., & Zhang, Y. (2018). PAYJIT: Space-optimal JIT compilation and its practical implementation. Proceedings of the 27th International Conference on Compiler Construction (CC’18), Vienna, Austria, 71-81. https://doi.org/10.1145/3178372.3179523
Chen, L., Xie, X., Fan, X., Ma, W., Zhang, H., & Zhou, H. (2003). A visual attention model for adapting images on small displays. ACM Multimedia Systems Journal, 9(4), 353–364. https://doi.org/10.1007/s00530-003-0105-4
Dargham, J. A., Chekima, A., Moung, E. G., & Omatu, S. (2018). A comparison of the YCBCR colour space with gray scale for face recognition for surveillance applications. Advances in Distributed Computing and Artificial Intelligence Journal, 7(2), 35-42. https://doi.org/10.14201/ADCAIJ2018724352
Fan, L., Song, F., & Jutamulia, S. (2007). Edge detection with large depth of focus using differential Haar–Gaussian wavelet transform. Optics Communications, 270(1), 169–175. https://doi.org/10.1016/j.optcom.2006.09.015
Garg, A., & Negi, A. (2020). A survey on content-aware image resizing methods. KSII Transactions on Internet and Information Systems, 14(7). https://doi.org/10.3837/tiis.2020.07.015
Jantz, M. R., & Kulkarni, P. A. (2013). Performance potential of optimization phase selection during dynamic JIT compilation. Proceedings of the 9th ACM SIGPLAN/SIGOPS International Conference on Virtual Execution Environments (VEE ’13), 131–140. https://doi.org/10.1145/2451512.2451539
Kao, P. B., & Nutter, B. (2006). Application of Maximum Entropy-Based Image Resizing to Biomedical Imaging. 19th IEEE Symposium on Computer-Based Medical Systems (CBMS’06). https://doi.org/10.1109/cbms.2006.46
Kawakibi, Z. M. (2022). Content-aware image resizing using a greedy seam carving algorithm. Makalah IF2211 Strategi Algoritma, Semester II Tahun 2021/2022.
Liaw, J.-J., Lu, C.-P., Huang, Y.-F., Liao, Y.-H., & Huang, S.-C. (2020). Improving Census Transform by High-Pass with Haar Wavelet Transform and Edge Detection. Sensors, 20(9), 2537. https://doi.org/10.3390/s20092537
Lin, X., Ma, Y., Ma, L., & Zhang, R. (2014). A survey for image resizing. Journal of Zhejiang University SCIENCE C, 15(9). https://doi.org/10.1631/jzus.C1400102
Manis, G., Aktaruzzaman, M., & Sassi, R. (2017). Bubble entropy: An entropy almost free of parameters. IEEE Transactions on Biomedical Engineering, 64(11), 2711-2718. https://doi.org/10.1109/TBME.2017.2664105
Mishiba, K., & Ikehara, M. (2011). Block-based seam carving. 2011 1st International Symposium on Access Spaces (ISAS). https://doi.org/10.1109/ISAS.2011.5960930
Noh, H., & Han, B. (2012). Seam carving with forward gradient difference maps. Proceedings of the 20th ACM International Conference on Multimedia, 709-712. https://doi.org/10.1145/2393347.2396293
Pal, R., & Tripathi, P. C. (2016). Content-aware image retargeting: A survey. In R. Pal (Ed.), Innovative research in attention modeling and computer vision applications (pp. 115-131). IGI Global. https://doi.org/10.4018/978-1-4666-8723-3.ch005
Polson, W. (2025, January 2). Common screen resolution for web design in 2025. Australian Internet Advertising. https://aiad.com.au/what-screen-resolution-should-one-design-for/
Pritch, Y., Kav-Venaki, E., & Peleg, S. (2009). Shift-map image editing. 2009 IEEE 12th International Conference on Computer Vision, 151-158. https://doi.org/10.1109/iccv.2009.5459159
Ribeiro, M., Henriques, T., Castro, L., Souto, A., Antunes, L., Costa-Santos, C., & Teixeira, A. (2021). The Entropy Universe. Entropy, 23(2), 222. https://doi.org/10.3390/e23020222
Rubinstein, M., Shamir, A., & Avidan, S. (2008). Improved seam carving for video retargeting. ACM Transactions on Graphics, 27(3), 16. https://doi.org/10.1145/1360612.1360615
Rubinstein, M., Shamir, A., & Avidan, S. (2009). Multi-operator media retargeting. ACM Transactions on Graphics, 28(3), 23. https://doi.org/10.1145/1531326.1531329
Suh, B., Ling, H., Bederson, B. B., & Jacobs, D. W. (2003). Automatic thumbnail cropping and its effectiveness. Proceedings of the 16th annual ACM symposium on User Interface Software and Technology (UIST ’03), 95–104. https://doi.org/10.1145/964696.964707
Tian, M., Wan, S., & Yue, L. (2007).A novel approach for change detection in remote sensing image based on saliency map. In Proceedings of the IEEE International Conference on Computer Graphics, Imaging and Visualisation (CGIV) (pp. 397–402). IEEE. https://doi.org/10.1109/CGIV.2007.11
Tsai, D.-Y., Lee, Y., & Matsuyama, E. (2007). Information Entropy Measure for Evaluation of Image Quality. Journal of Digital Imaging, 21(3), 338–347. https://doi.org/10.1007/s10278-007-9044-5
Wang, Y.-S., Tai, C.-L., Sorkine, O., & Lee, T.-Y. (2008). Optimized scale-and-stretch for image resizing. ACM Transactions on Graphics, 27(5), 118. https://doi.org/10.1145/1409060.1409071
Wolf, L., Guttmann, M., & Cohen-Or, D. (2007). Nonhomogeneous content-driven video-retargeting. Proceedings of the Eleventh IEEE International Conference on Computer Vision (ICCV). https://doi.org/10.1109/ICCV.2007.4409010
Zhang, Y. F., Hu, S. M., & Martin, R. R. (2008). Shrinkability maps for content-aware video resizing. Computer Graphics Forum, 27(7), 1797–1804. https://doi.org/10.1111/j.1467-8659.2008.01325.x
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
License:
This work is licensed under a Creative Commons Attribution (CC BY 4.0) International License.
Find this article in:
Most read articles in this journal
- Modern love lines: An inquiry on experiences and generational views on online dating and relationships
- Measuring the impact of Pantawid Pamilyang Pilipino Program on health and education in Maangas Presentacion, Camarines Sur: A regression discontinuity design approach
- Assessing mother’s knowledge and attitude on routine immunization: A cross-sectional study at Kalinga provincial hospital
- Readify: Interactive e-story book to improve English reading comprehension skills
- Bridging the gap: Examining HUMSS students’ perceptions of sampling in statistics
- Transition from online to onsite learning: Standpoints of college students in a government-funded institution
- APeriod Go: Educational board game for students’ engagement
- Translated effect on the integration of gamification to students’ learning engagement
- Does an agricultural intervention impact the socio-economic development of farmers in upland barangays of Goa, Camarines Sur? Evidence from regression discontinuity design
- Genre of college students’ social media posts: An analysis