Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Iannarelli's studies demonstrated that ear shape represents a biometric identifier able to authenticate people in the same way as more established biometrics, like face or voice for instance. Hover, not many researches can be found in literature about ear recognition. In most cases existing algorithms are borrod from other biometric contexts. An example is PCA (Principal Component Analysis). Eigen-ears only provide high recognition rate in closely controlled conditions, while performances decay even for small changes in environmental conditions.  propose a fractal based technique, namely HERO (Human Ear Recognition against Occlusions) to classify human ears. The feature extraction process has been made local, so that the system gets robust with respect to small changes in pose/illumination and partial occlusions. Experimental results confirm the superiority of this approach over several linear and non linear techniques.
['Maria De Marsico', 'Nappi Michele', 'Daniel Riccio']
I am writing a research paper on a idea HERO: Human Ear Recognition against Occlusions
[{"from": "human", "value": "I am writing a research paper on a idea HERO: Human Ear Recognition against Occlusions"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Iannarelli's studies demonstrated that ear shape represents a biometric identifier able to authenticate people in the same way as more established biometrics, like face or voice for instance. Hover, not many researches can be found in literature about ear recognition. In most cases existing algorithms are borrod from other biometric contexts. An example is PCA (Principal Component Analysis). Eigen-ears only provide high recognition rate in closely controlled conditions, while performances decay even for small changes in environmental conditions.  propose a fractal based technique, namely HERO (Human Ear Recognition against Occlusions) to classify human ears. The feature extraction process has been made local, so that the system gets robust with respect to small changes in pose/illumination and partial occlusions. Experimental results confirm the superiority of this approach over several linear and non linear techniques."}]