SIGNAL CHECKING OF STEGANO INSERTED ON IMAGE DATA CLASSIFICATION BY NFES-MODEL

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Published May 10, 2012
DOI https://doi.org/10.33050/ccit.v5i3.158

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M. Givi Efgivia Safaruddin A. Prasad Al-Bahra .LB

Abstract

Abstract. In this paper, we propose an identification method of the land cover from remote sensing data with combining neuro-fuzzy and expert system. This combining then is called by Neuro-Fuzzy Expert System Model (NFES-Model). A Neural network (NN) is a part from neuro-fuzzy has the ability to recognize complex patterns, and classifies them into many desired classes. However, the neural network might produce misclassification. By adding fuzzy expert system into NN using geographic knowledge based, then misclassification can be decreased, with the result that improvement of classification result, compared with a neural network approximation. An image data classification result may be obtained the secret information with the inserted by steganography method and other encryption. For the known of secret information, we use a fast fourier transform method to detection of existence of that information by signal analyzing technique.

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How to Cite
[1]
M. Efgivia, S. Prasad, and A.-B. .LB, “SIGNAL CHECKING OF STEGANO INSERTED ON IMAGE DATA CLASSIFICATION BY NFES-MODEL”, CCIT (Creative Communication and Innovative Technology) Journal, vol. 5, no. 3, pp. 312-328, May 2012.
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Vol 5 No 3 (2012): CCIT JOURNAL
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Articles

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