Filtering and Wavelet Transform Algorithm for Old Document Image Restoration
DOI:
https://doi.org/10.21512/comtech.v8i3.3995Keywords:
old document, image restoration, filtering, wavelet transformAbstract
The aim of this research was to develop image restoration system using filtering and wavelet transform algorithm. Data collection was through observation and system was developed using prototyping model. Result of this research is a computer based on system to restore image containing noise. Based on the research process, filtering and wavelet transform algorithm can used to restore old document image from interferences (noise).
Plum Analytics
References
Feng, Y., Lu, H., & Zeng, X. (2015). Image restoration based on hybrid ant colony algorithm. TELKOMNIKA (Telecommunication Computing Electronics and Control), 13(4), 1298-1304.
Gülcü, Ş., Mahi, M., Baykan, Ö. K., & Kodaz, H. (2016). A parallel cooperative hybrid method based on ant colony optimization and 3-Opt algorithm for solving traveling salesman problem. Soft Computing, 20(11), 1-17.
Hetal, J.V., & Astha, B. (2013). A Review on Otsu image segmentation algorithm. IJARCET (International Journal of Advanced Research in Computer Engineering & Technology), 2(2), 387-389
Hinami, R., Liu, X., Chiba, N., & Satoh, S. I. (2016). Bidirectional extraction and recognition of scene text with layout consistency. International Journal on Document Analysis and Recognition (IJDAR), 19(2), 83-98.
Hou, X., Yang, J., Jiang, G., & Qian, X. (2013). Complex SAR image compression based on directional lifting wavelet transform with high clustering capability. IEEE Transactions on Geoscience and Remote Sensing, 51(1), 527-538.
Huiyu, Z., Jiahua, W., & Jianguo. Z (2010). Digital image processing: Part 1. Retrieved from www.bookboon.com
Konidaris, T., Kesidis, A. L., & Gatos, B. (2016). A segmentation-free word spotting method for historical printed documents. Pattern Analysis and Applications, 19(4), 963-976.
Rafael, C. G., & Richard, E. W. (2008). Digital image processing. USA: Addison-Wesley.
Ren, J., Lu, H., & Zeng, X. (2015). Image Denoising Based on K-means Singular Value Decomposition. TELKOMNIKA (Telecommunication Computing Electronics and Control), 13(4), 1312-1318.
Trieu, D. B. K., & Maruyama, T. (2015). Real-time color image segmentation based on mean shift algorithm using an FPGA. Journal of Real-Time Image Processing, 10(2), 345-356.
Wang, X. (2010). Recovery of blurring scanned manuscript image based on wavelets transform algorithm. In 3rd International Congress on Image and Signal Processing (CISP) (pp. 844-847). IEEE.
Downloads
Published
Issue
Section
License
Authors who publish with this journal agree to the following terms:
a. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License - Share Alike that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
b. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
c. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
USER RIGHTS
All articles published Open Access will be immediately and permanently free for everyone to read and download. We are continuously working with our author communities to select the best choice of license options, currently being defined for this journal as follows: