Janarthanam, S., Ramalingam, M. and Narendran, P. (2010) Texture Analysis on Low Resolution Images Using Unsupervised Segmentation Algorithm with Multichannel Local Frequency Analysis. International Conference on Communication and Computational Intelligence (INCOCCI), 4-6 January 2010, 260-265.

has been cited by the following article:

• TITLE: Target Image Classification through Encryption Algorithm Based on the Biological Features

  AUTHORS: Zhiwu Chen, Qing E. Wu, Weidong Yang

  KEYWORDS: Encryption, Palm Recognition, Classification, Feature Extraction

  JOURNAL NAME: International Journal of Intelligence Science, Vol.5 No.1, December 22, 2014

  ABSTRACT: In order to effectively make biological image classification and identification, this paper studies the biological owned characteristics, gives an encryption algorithm, and presents a biological classification algorithm based on the encryption process. Through studying the composition characteristics of palm, this paper uses the biological classification algorithm to carry out the classification or recognition of palm, improves the accuracy and efficiency of the existing biological classification and recognition approaches, and compares it with existing main approaches of palm classification by experiments. Experimental results show that this classification approach has the better classification effect, the faster computing speed and the higher classification rate which is improved averagely by 1.46% than those of the main classification approaches.