Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A novel approach of Gabor feature based face recognition approach is presented in this paper. Gabor wavelet is a very porful tool to analyze the texture of an image. Due to its characteristic of being insensitive to the varying illumination condition, it also has been widely used in face recognition task. Hover, the redundancy of Gabor feature limited its application. , a feature mask is applied for the sub-sampling of the original magnitude feature of Gabor transform. What's more, a lately algorithm of discrimination, Direct Fractional-Step LDA, is adopted instead of traditional method of PCA+LDA. It preserved more important discriminate information during reducing dimensions. The experiment results indicate that the performance is superior to single DF-LDA and the method based on low-dimensional Gabor feature with PCA+LDA.
['Zhang Yong Mei', 'Zhang Xing Ming', 'GuoYuCong']
I am writing a research paper on a idea Face recognition base on low dimension Gabor feature using direct fractional-step LDA
[{"from": "human", "value": "I am writing a research paper on a idea Face recognition base on low dimension Gabor feature using direct fractional-step LDA"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A novel approach of Gabor feature based face recognition approach is presented in this paper. Gabor wavelet is a very porful tool to analyze the texture of an image. Due to its characteristic of being insensitive to the varying illumination condition, it also has been widely used in face recognition task. Hover, the redundancy of Gabor feature limited its application. , a feature mask is applied for the sub-sampling of the original magnitude feature of Gabor transform. What's more, a lately algorithm of discrimination, Direct Fractional-Step LDA, is adopted instead of traditional method of PCA+LDA. It preserved more important discriminate information during reducing dimensions. The experiment results indicate that the performance is superior to single DF-LDA and the method based on low-dimensional Gabor feature with PCA+LDA."}]