Abstract: Image retrieval method based on Euclidian distance between normalized features with their mean and variance in feature space is proposed. Effectiveness of the normalization is evaluated together with a validation of the proposed image retrieval method. The proposed method is applied for discrimination and identifying dangerous red tide species based on wavelet utilized classification methods together with texture and color features. Through experiments, it is found that classification performance with the proposed wavelet derived shape information extracted from the microscopic view of the phytoplankton is effective for identifying dangerous red tide species among the other red tide species rather than the other conventional texture, color information. Moreover, it is also found that the proposed normalization of features is effective to improve identification performance.

Kohei Arai , “Image Retrieval and Classification Method Based on Euclidian Distance Between Normalized Features Including Wavelet Descriptor” International Journal of Advanced Research in Artificial Intelligence(IJARAI), 2(10), 2013. http://dx.doi.org/10.14569/IJARAI.2013.021004

@article{2013,
title = {Image Retrieval and Classification Method Based on Euclidian Distance Between Normalized Features Including Wavelet Descriptor},
journal = {International Journal of Advanced Research in Artificial Intelligence},
doi = {10.14569/IJARAI.2013.021004},
url = {http://dx.doi.org/10.14569/IJARAI.2013.021004},
year = {2013},
publisher = {The Science and Information Organization},
volume = {2},
number = {10},
author = {Kohei Arai }
}