Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Reference point identification is important in automatic fingerprint recognition system as it can be used to align fingerprints in a correct orientation in spite of the possibility of different transformations in fingerprint images. It is also used in fingerprint classification, as it is desirable to classify fingerprint images for forensic type applications which require the input image to be verified against a large database. The important feature information useful for classification is centered near the reference point. Most of the current approaches for identifying the reference point either require determining ridge orientation or use some complex filters. These methods either operate on 2D (two dimensional) or are not robust to rotation or cannot be applied to every class of fingerprint image.  proposes a method to reliably identify unique reference point that operates in 1D (one dimensional). The method treats the fingerprint ridges as a non-overlapped sequence of chain code segments. A modified k-curvature method has been proposed to find the high-curvature area of fingerprint ridges. The reference point localization is based on the property of the ridge’s bending energy. The proposed method is tested on FVC2002 and FVC2004 standard datasets, and the experimental results show that the proposed algorithm can accurately locate reference point for all types of fingerprint images.
['Geevar C. Zacharias', 'Madhu S. Nair', 'P. Sojan Lal']
I am writing a research paper on a idea Fingerprint reference point identification based on chain encoded discrete curvature and bending energy
[{"from": "human", "value": "I am writing a research paper on a idea Fingerprint reference point identification based on chain encoded discrete curvature and bending energy"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Reference point identification is important in automatic fingerprint recognition system as it can be used to align fingerprints in a correct orientation in spite of the possibility of different transformations in fingerprint images. It is also used in fingerprint classification, as it is desirable to classify fingerprint images for forensic type applications which require the input image to be verified against a large database. The important feature information useful for classification is centered near the reference point. Most of the current approaches for identifying the reference point either require determining ridge orientation or use some complex filters. These methods either operate on 2D (two dimensional) or are not robust to rotation or cannot be applied to every class of fingerprint image.  proposes a method to reliably identify unique reference point that operates in 1D (one dimensional). The method treats the fingerprint ridges as a non-overlapped sequence of chain code segments. A modified k-curvature method has been proposed to find the high-curvature area of fingerprint ridges. The reference point localization is based on the property of the ridge\u2019s bending energy. The proposed method is tested on FVC2002 and FVC2004 standard datasets, and the experimental results show that the proposed algorithm can accurately locate reference point for all types of fingerprint images."}]