Image analysis – Image compression or coding
Reexamination Certificate
1999-04-21
2003-05-27
Do, Anh Hong (Department: 2721)
Image analysis
Image compression or coding
C382S125000, C382S257000
Reexamination Certificate
active
06571014
ABSTRACT:
FIELD OF THE INVENTION
The present invention relates to the digital compression of images and, in particular, to an efficient method of representing the essence of an image as a phase modulated structure. The present invention finds application in the coding of a variety of images, and is of particular relevance to the representation of “fingerprint” type images.
BACKGROUND ART
The compression of grey-scale fingerprint images is an important problem in the field of digital image compression. In one recent proposal utilised by the United States Federal Bureau of Investigation (FBI), an algorithm based on a scalar quantisation of a discrete wavelet transform decomposition of the image, followed by run length encoding and Huffman encoding has been implemented. For an example of discussion of the technique utilised, see “Compression of Gray-Scale Fingerprint Images” by Tom Hopper appearing in SPIE Vol. 2242, entitled Wavelet Applications (1994) at pp 180-187. The reported compression factors for the wavelet based compression were typically 15:1, and at best about 20:1.
Fingerprint ridges are not necessarily continuous across an impression but suffer interruptions such as ridge endings or bifurcations. Collectively, these interruptions are known as minutiae. The definitive information utilised to determine whether one fingerprint matches another is the fine detail in these ridges—the minutiae and their relationships. Hence, it is normally considered important that for fingerprint compression applications that the fidelity of the ridge detail is retained in the compression and decompression transformations.
The process of fingerprint identification (matching) and fingerprint image compression are based on two unrelated methods. The typical compression scheme utilised is wavelet compression. The wavelet compression schemes are essentially general image compression schemes and do not take advantage of the particular structure of a fingerprint image. The matching schemes characterise the minutiae by type, orientation and position. These features are then catalogued and stored as essentially separate data to the compressed image. Automatic fingerprint identification is achieved by comparing a list of the catalogued features with a data base of stored lists. When a match is detected, the “matching” fingerprint is decompressed for direct comparison with the fingerprint in question.
Whilst such an arrangement affords fast high-level matching, the fine detail that characterises the minutiae is not considered until the more time consuming direct comparison. Significantly, although the catalogued features may be thought of as compressed data, such does not represent the compressed image and it is desirable for matching to be based on the image, rather than some catalogued summary thereof. It is thus desirable to provide for a system that provides for high compression ratios whilst permitting the automatic classification of minutiae, thus promoting automatic matching systems.
SUMMARY OF THE INVENTION
In accordance with a first aspect of the present invention, there is provided a method of encoding an image, the method comprising the steps of determining a phase map structure for the image; and encoding the phase map structure.
In accordance with a second aspect of the present invention, there is provided a method of encoding an image, the method comprising the steps of determining a phase map structure for the image; removing any singularities in the phase map structure to create a continuous phase map structure; and separately encoding the singularities and the continuous phase map structure as an encoded representation of the image.
Preferably, the singularity encoding includes encoding a position of each singularity in addition to its order and orientation. The phase map structure can be of the form:
ƒ(
x,y
)=
a
(
x,y
)+
b
(
x,y
)cos(&phgr;(
x,y
))+
c
(
x,y
)+
n
(
x,y
)
The magnitude of the phase modulated component can be separately encoded as what is termed herein a “significance map”. The significance map represents the relative importance of all phase components. Advantageously the image is a fingerprint-type image.
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Canon Kabushiki Kaisha
Do Anh Hong
Fitzpatrick ,Cella, Harper & Scinto
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