The new proposed method for texture modification of closed up face image based on image processing using local weighting pattern (LWP) with enhancement technique

  • Authors

    • Achmad Fanany Onnilita Gaffar
    • Darius Shyafary
    • Rony H
    • Arief Baramanto Wicaksono Putra
    2018-03-05
    https://doi.org/10.14419/ijet.v7i2.2.12742
  • texture image, LWP method, log function
  • Abstract

    The texture is a two- and three-dimensional design element that is distinguished by the visual and physical properties perceived. Textured areas in the image can be marked with uniform or varying spatial intensity distribution. There are many techniques and methods from simple to sophisticated which available including machine learning-based methods to modify the texture map. The texture feature description becomes a new challenge in the field of computer vision and pattern recognition since the emergence of the local pattern binary method (LBP). This study proposes a new method called Local Weighting Pattern (LWP) for modifying textures based on the pixel's neighborhood of an RGB image. The results of this study obtained that LWP method produces a texture with a unique and artistic visualization. The Log function has been used to improve the image quality of the LWP method.

     

     

  • References

    1. [1] S. Fekri-Ershad, "Innovative Texture Database Collecting Approach and Feature Extraction Method based on Combination of Gray Tone Difference Matrixes, Local Binary Patterns, and K-means Clustering," presented at the First National Conference on Computer, Information Technology and Communication (CCITC 2014), Marvdasht, Fars, Iran, (2014).

      [2] A. Rahim, N. Hossain, T. Wahid, and S. Azam, "Face Recognition using Local Binary Patterns (LBP)," Global Journal of Computer Science and Technology Graphics & Vision, vol. 13, (2013).

      [3] L. Liu, S. Lao, P. W. Fieguth, Y. Guo, X. Wang, and M. Pietikäinen, "Median Robust Extended Local Binary Pattern for Texture Classification," IEEE TRANSACTIONS ON IMAGE PROCESSING, (2016).

      [4] P. B. PATINGE and C. N.DESHMUKH, "Local Binary Pattern Base Face Recognition System," International Journal of Science, Engineering and Technology Research (IJSETR), vol. 4, pp. 1356-1361, (2015).

      [5] S. Wan, H.-C. Lee, X. Huang, T. Xu, T. Xu, X. Zeng, Z. Zhang, Y. Sheikine, J. L. Connolly, J. G. Fujimoto, and C. Zhou, "Integrated local binary pattern texture features for classification of breast tissue imaged by optical coherence microscopy," Medical Image Analysis, vol. 38, pp. 104-116, (2017).

      [6] A. H. H. Alasadi and R. H. Jaffar, "Fingerprint Verification System based on Active Forgery Techniques," International Journal of Computer Applications (IJCA), vol. 180, (2018).

      [7] K. I. Alsaif and R. H. Hamid, "Study the Effect of Threshold Value on Object Detection," International Journal of Computer Applications (IJCA), vol. 179, (2018).

      [8] S. G. Bhable, S. Tharewal, and H. Gite, "Review on Face, Ear and Signature for Human Identification," International Journal of Computer Applications (IJCA), vol. 180, (2018).

      [9] B. B. Gabhale, M. S. Shinde, A. M. Kamble, and V.C.Kulloli4, "Tongue Image Analysis with Color and Gist Features for Diabetes Diagnosis.," International Research Journal of Engineering and Technology (IRJET), vol. 4, pp. 523-526, (2017).

      [10] U. Jindal, S. Dalal, and N. Dahiya, "A combine approach of preprocessing in integrated signature verification (ISV)," International Journal of Engineering & Technology (IJET), vol. 7, pp. 155-159, (2018).

      [11] S. K. P.S and D. V.S, "Extraction of Texture Features using GLCM and Shape Features using Connected Regions," International Journal of Engineering and Technology, vol. 8, pp. 2926-2930, (2016).

      [12] M. G. Saeed, F. L. Malallah, and Z. A. Aljawaryy, "Content-Based Image Retrieval by Multi-Features Extraction and K-Means Clustering," International Journal of Electrical, Electronics and Computers, vol. 2, pp. 1-11, (2017).

      [13] N. Saffazura, A. Safuan, M. Ismail, and N. Jamil, "Feature Extraction Technique for Human Gait Video Analysis," Journal of Engineering and Applied Sciences, vol. 12, pp. 534-541, (2017).

      [14] M. R. Wankhade and N. M. Wagdarikar, "Feature Extraction of Edge Detected Images," International Journal of Computer Science and Mobile Computing (IJCSMC), vol. 6, pp. 336-345, (2017).

      [15] P. R. Chavan and D. J. Pete, "Face Recognition using Local Derivative Pattern Face Descriptor," International Journal Of Engineering And Computer Science (IJECS), vol. 3, pp. 8830-8834, (2014).

      [16] V. S. K. Gangavarapu and G. K. M. Pillutla, "Local Tri-directional Weber Patterns: A New Descriptor for Texture and Face Image Retrieval," international Journal of Computer Science and Information Technologies (ICSIT), vol. 7, pp. 1571-1577, (2016).

      [17] S. Gupta, "An Efficient Feature Selection Technique using Genetic Algorithm for Activity Recognition of Elder People," International Journal of Computer Applications (IJCA), vol. 179, (2017).

      [18] M. Nirgude and S. Gengaje, "Iris Recognition System based on Multi-resolution Analysis and Support Vector Machine," International Journal of Computer Applications (IJCA), vol. 173, (2017).

      [19] S. Almas, L. S. A., T. L., and D. P. D., "Feature Level Fusion for Fingerprint using Neural Network for Person Identification," International Journal of Computer Applications (IJCA), (2016).

      [20] S. Chabert, T. Mardones, R. Riveros, M. Godoy, A. Veloz, R. Salas, and P. Cox, "Applying machine learning and image feature extraction techniques to the problem of cerebral aneurysm rupture," Research Ideas and Outcomes, vol. 3, p. e11731, (2017).

      [21] A. Tayfour Ahmed, A. Mohammed, and M. Yahia, "Performance comparisons of artificial neural network algorithms in facial expression recognition," International Journal of Engineering & Technology, vol. 4, p. 465, (2015).

      [22] D. Wen, H. Han, and A. K. Jain, "Face Spoof Detection with Image Distortion Analysis," IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, (2015).

      [23] M. R. JOSHI and R. A. KARKADE, "A survey on a mosaic image creation for secure secret image transmission," International Journal of Computer Science and Mobile Computing (IJCSMC), vol. 5, pp. 89-95, (2016).

      [24] P. M.Jain and V. K.Shandliya, "A Review Paper on Various Approaches for Image Mosaicing," International Journal of Computational Engineering Research (IJCER), vol. 3, pp. 106-109, (2013).

      [25] X. Shao, C. Xu, and J. H. Lim, "Image Mosaics Base on Homogeneous Coordinates," presented at the Conferences in Research and Practice in Information Technology, Australia, (2003).

      [26] S. K. and S. S, "Image Enhancement Using Fuzzy Logic," IOSR Journal of Electronics and Communication Engineering (IOSR-JECE), pp. 34-44, (2017).

      [27] M. Khandelwal, S. Saxena, and P. Bharti, "An Efficient Algorithm for Image Enhancement," Indian Journal of Computer Science and Engineering (IJCSE), vol. 2, pp. 118-123, (2005).

      [28] W. Zuo, L. Zhang, C. Song, and D. Zhang, "Texture Enhanced Image Denoising via Gradient Histogram Preservation," CVPR2013 - Computer Vision Foundation - IEEE Xplore, pp. 1203-1210, (2013).

  • Downloads

  • How to Cite

    Fanany Onnilita Gaffar, A., Shyafary, D., H, R., & Baramanto Wicaksono Putra, A. (2018). The new proposed method for texture modification of closed up face image based on image processing using local weighting pattern (LWP) with enhancement technique. International Journal of Engineering & Technology, 7(2.2), 94-98. https://doi.org/10.14419/ijet.v7i2.2.12742

    Received date: 2018-05-12

    Accepted date: 2018-05-12

    Published date: 2018-03-05