Image Compression Based on Crucial Region for Radiographic Weldment Images

(*) Corresponding author

Authors' affiliations

DOI's assignment:
the author of the article can submit here a request for assignment of a DOI number to this resource!
Cost of the service: euros 10,00 (for a DOI)


Radiographic images are generally of high volume. These images when stored occupy a lot of storage space and the transmission of them is also difficult due their large size. So reduction of size plays an important role in storage and transmission of images. To achieve this reduction, compression techniques are being widely used.  This paper focuses on the process of welding, Tungsten Inert Gas (TIG) welding in specific, the generation and development of photographic film of weldments and also a novel method is presented, which is intended to reduce the size of the radiographic image developed, by applying lossless compression technique on the crucial regions of the image. The crucial regions of the image are automatically detected by using segmentation technique in the proposed method. After the detection of crucial regions, lossless compression technique is applied on them. The compressed data obtained along with some information of the image is transmitted to the other validated user for reconstruction of the original image. Apparently, the original image data can’t be understood by the third party during transmission, which makes this method to be used for secure transmission of data. The image reconstructed by this method will not have any loss of data in the crucial regions of the image but certain loss is present in the non-crucial regions. This method is tested on some images and their results are shown in the paper along with the compression rates. The results are also compared with other methods.
Copyright © 2013 Praise Worthy Prize - All rights reserved.


TIG Welding; Radiographic Images; Huffman; Lossless Compression; Entropy

Full Text:



Lin, Q., Ou, C, Tsallis entropy and the long-range correlation in image thresholding, Signal Processing, Vol. 92 n. 12, 2012, pp. 2931 – 2939.

Ma, S., A digital image compression algorithm based on gene expressions, , International Review on Computers and Software, Vol. 7 n 5, 2012, pp. 2555-2559.

Ho, K.S., Gan, T.H., Billson, D.R., Hutchins, D.A., Application of pulse compression signal processing techniques to electromagnetic acoustic transducers for noncontact thickness measurements and imaging, Review of Scientific Instruments, Vol. 76 n. 5,2005.

Zhong, J., Shiraga, H., Azechi, H., One-dimensional and multichannels multi-imaging x-ray streak camera for imploded core plasma of shell-cone target, Review of Scientific Instruments Vol. 79 n. 10, 2008.

Kang, B.J., Kim, H.S., Park, C.S., Choi, J.J., Lee, J.H., Choi, B.G., Acceptable compression ratio of full-field digital mammography using JPEG 2000, Clinical Radiology Vol. 66 n. 7, 2011, pp. 609-613.

Gianola, D.S., Sedlmayr, A., Mnig, R., Volkert, C.A., Major, R.C., Cyrankowski, E., Asif, S.A.S., (...), Kraft, O., In situ nanomechanical testing in focused ion beam and scanning electron microscopes, Review of Scientific Instruments Vol. 82 n. 6, 2011.

Chen, Chang Wen, Zhang, Ya-Qin, Parker, Kevin J., Subband analysis and synthesis of volumetric medical images using wavelet, Proceedings of SPIE - The International Society for Optical Engineering, 1994, Chicago,USA.

Chen, Chang Wen, Zhang, Ya-Qin, Luo, Jiebo, Parker, Kevin J., Medical image compression with structure-preserving adaptive quantization, Proceedings of SPIE - The International Society for Optical Engineering, 1995, Chicago,USA.

Strom, J., Cosman, P.C., Medical image compression with lossless regions of interest, Signal Processing Vol. 59 n. 2 , 1997, pp. 155-17.

Li, X., Orchard, M.T., New edge-directed interpolation, IEEE Transactions on Image Processing Vol. 10 n. 10, 2001, pp. 1521-1527.

Zukoski, M.J., Boult, T., Iyriboz, T., A novel approach to medical image compression, International Journal of Bioinformatics Research and Applications Vol. 2 n. 1 , 2006, pp. 89-103.

Dai, V., Zakhor, A., Lossless Compression of VLSI Layout Image Data, IEEE Trans. on Image Processing, Vol. 15n. 9, 2006 , pp. 2522-2530.

Sun, W., Lu, Y., Wu, F., Li, S., Level embedded medical image compression based on value of interest, Proceedings - International Conference on Image Processing,2009, Cairo, Eypt.

Nhu, Q.T., Huynh, C.X., Dang, T.T., Lossless image compression using ideal cross point regions with wavelet transform, 4th International Conference on Biomedical Engineering, 2013, Vietnam.

Kreizer, M., Liberzon, A., Three-dimensional particle tracking method using FPGA-based real-time image processing and four-view image splitter, Experiments in Fluids Vol. 50 n.3 , 2011,pp. 613-620.

Chan, K.-Y., Stich, D., Voth, G.A., Real-time image compression for high-speed particle tracking, Review of Scientific Instruments Vol. 78 n. 2 , 2007.

E.R. Bohnart, TIG Handbook for GTAW Gas Tungsten Arc Welding (Miller Electric. 2005).


  • There are currently no refbacks.

Please send any question about this web site to
Copyright © 2005-2024 Praise Worthy Prize