Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Fingerprint representations can be broadly divided into three categories: image level, texture features and minu- tiae features. Both image based and texture based repre- sentations require accurate alignment before comparison. This presents a problem since accurate registration of fin- gerprints is challenging. On the other hand, minutiae based matchers are invariant to changes in orientation and posi- tion, but completely ignore the rich visual content in the image. ,  present a localized texture based representation scheme that relies solely on visual content for identification and at the same time does not require ab- solute alignment.  outline techniques to efficiently com- pute these features and also propose an algorithm to per- form identification based on these features. Our experimen- tal evaluations over database of several sizes show that the proposed features are both accurate and scalable.
['Sharat Chikkerur', 'Sharath Pankanti', 'Alan Jea', 'Nalini K. Ratha', 'Ruud M. Bolle']
I am writing a research paper on a idea Fingerprint Representation Using Localized Texture Features
[{"from": "human", "value": "I am writing a research paper on a idea Fingerprint Representation Using Localized Texture Features"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Fingerprint representations can be broadly divided into three categories: image level, texture features and minu- tiae features. Both image based and texture based repre- sentations require accurate alignment before comparison. This presents a problem since accurate registration of fin- gerprints is challenging. On the other hand, minutiae based matchers are invariant to changes in orientation and posi- tion, but completely ignore the rich visual content in the image. ,  present a localized texture based representation scheme that relies solely on visual content for identification and at the same time does not require ab- solute alignment.  outline techniques to efficiently com- pute these features and also propose an algorithm to per- form identification based on these features. Our experimen- tal evaluations over database of several sizes show that the proposed features are both accurate and scalable."}]