Abstrak |
: |
Exploration is a main process in the nickel mining activities. One of the most important steps in exploration is obtain soil samples (cores) to determine the potential of nickel in the soil. Laboratory testing is a way to know how much the nickel content on the core. This research aims to utilize the core image of the statistical characteristics of color and texture, Biplot analysis using SVD, K-Means and identification using SVM method with RBF kernel and polynomial to determine the potential of nickel.
|
Bibliography |
: |
- Simanjuntak. Determination of Nickel Content on Sediment stratigraphy laterite. 1994.
- Hazria. Laterite nickel in sediments. 2007.
- Rudi Suryadi. Determination of Nickel Content on Sediment stratigraphy laterite in Kendari. Thesis. Surabaya: University Haluoleo; 2011.
- Yang Jiang and Zhang David. A New Approach to Appearance-Based Face Representation and Recognition. IEEE Transaction on Pattern Analysis and Machine on Intelligence. 2004; 26(1): 1-9.
- Le Thai Hoang, Bui Len. Face Recognition Based on SVM and 2DPCA. International Journal of Signal Procesing, Image and Pattern Recognition Procesing. 2011; 4(3): 85-93.
- Martinez, WL and Martinez, AR. Computational Statistics Handbook with Matlab. CRC Press LLC Florida. 2002.
- Abdul Kadir and AdhiSusanto. Theory and Application of Image Processing. Andi Yogyakarta. 2013.
- Haralic RM, K Shanmugam, ItshakDinstein. Image texture classification. IEEE Transactions on Systems, Man and Cybernetics. 1973; 3(6).
- Kulkarni, AD. Artificial Neural Network for Image Understanding. Van Nostrand Reinhold, New York. 1994.
- Hall-Bayer, M. HIS Co-representation of circular and non-circular variables using harmonic analysis parameter. Canadian Journal of Remote Sensing. 2007; 33(5): 416-421. (in this case Vol.33, Issues 4, and page 416-421).
- Newsam S, Kammath C. Comparing Shape and Texture Fitures for Pattern Recognition in the Simulation Data. On the IS&T/SPIE 'S Annual Symposium on Electronic Imaging. San Jose, USA. 2005.
|