Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  examine the problem of how to discriminate beten objects of more than two classes using psilaminimum informationpsila.  presents an efficient face recognition system, based on discrete cosine transform (DCT) and support vector machines (SVM). The idea is to reduce dimensionality of face space. DCT is used to extract pertinent information which represent low frequency in each block. Then the extracted DCT coefficients are used as features for the classification process, which is performed using SVM. The proposed approach was thoroughly tested, using ORL face databases. The obtained results are very encouraging, outperforming traditional methods like PCA, LDA or DCT based MLP in recognition systems.
['Aouatif Amine', 'Sanaa Ghouzali', 'Mohammed Rziza', 'Driss Aboutajdine']
I am writing a research paper on a idea Investigation of feature dimension reduction based DCT/SVM for face recognition
[{"from": "human", "value": "I am writing a research paper on a idea Investigation of feature dimension reduction based DCT/SVM for face recognition"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  examine the problem of how to discriminate beten objects of more than two classes using psilaminimum informationpsila.  presents an efficient face recognition system, based on discrete cosine transform (DCT) and support vector machines (SVM). The idea is to reduce dimensionality of face space. DCT is used to extract pertinent information which represent low frequency in each block. Then the extracted DCT coefficients are used as features for the classification process, which is performed using SVM. The proposed approach was thoroughly tested, using ORL face databases. The obtained results are very encouraging, outperforming traditional methods like PCA, LDA or DCT based MLP in recognition systems."}]