Abstract
This paper describes methods that optimize Gabor wavelet encoding scheme using Genetic algorism. Gabor wavelet is known very effective that extract important characteristic in object recognition. This paper presents, using the Genetic algorithm, an optimization methodology of the Gabor encoding scheme so that it produces characteristic vectors effective for the object recognition task. Most previous object recognition approaches using Gabor wavelet do not include careful and systematic optimization of the design parameters for the Gabor kernel, even though the system might be much sensitive to the characteristics of the Gabor encoding scheme. Purpose of this paper investigates geometrical position of Gabor Encode schema and fiducial points for efficient object recognition. Face images in the class of well-defined image objects are used. The superiority of the proposed system is shown using IT-Lab and FERET. The experiment performed with the proposed system exceeds those of most popular methods.
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Jeon, I., Kwon, K., Rhee, PK. (2004). Optimal Gabor Encoding Scheme for Face Recognition Using Genetic Algorithm. In: Negoita, M.G., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2004. Lecture Notes in Computer Science(), vol 3214. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30133-2_30
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DOI: https://doi.org/10.1007/978-3-540-30133-2_30
Publisher Name: Springer, Berlin, Heidelberg
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