Non-minutiae automatic fingerprint identification system and methods

Claim 1

A method for the automatic non-minutiae identification of a fingerprint of a person to be identified, comprising the steps of: video scanning an image of a fingerprint and producing fingerprint image data and whitespace data; electronically storing in digital form, in an addressable memory, said fingerprint image data and whitespace data; determining the location of the said fingerprint image data stored in digital form in said addressable memory with the said whitespace data; image framing the said fingerprint image data and whitespace data to a predetermined dimension, and establishing Y-TOP and Y-BOTTOM values along the Y-axis of said predetermined dimension; computing the X-Axis Range of the fingerprint image data contained in the framed image data by determining two X-axis values, said X-axis values being X-START and X-END, wherein X-START indicates the memory data location where the fingerprint image data starts on the X-axis, and X-END indicates the memory data location where the fingerprint image data ends on the X-axis; computing the Y-Axis Range of the fingerprint image data contained in the framed image data by determining two Y-axis values, said Y-axis values being Y-START and Y-END, wherein in Y-START indicates the memory data location where the fingerprint image data starts on the Y-axis, and Y-END indicates the memory data location where the fingerprint image data ends on the Y-axis; determining the dimensional area of said fingerprint image data by utilizing said X-START, X-END, Y-START and Y-END values; defining a fingerprint identity window within said fingerprint image data; defining said whitespace data as having a predetermined greylevel value; defining said fingerprint image data as having a second predetermined greylevel value distinct from that defined for the said whitespace data; as to said image framing, examining memory data locations (128, Y) where 0≦Y≦255, and upon finding three consecutive rows of whitespace data, defining Y-TOP as the latter examined data row Y-axis value, and examining memory data locations (128, Y) where 255≧Y≧0 and upon finding three consecutive rows of whitespace data, defining Y-BOTTOM as the last examined data row Y-axis value; computing the X-Axis Range of the framed image data to indicate the start and end memory locations of the fingerprint image data on the X-axis by determining X-START and X-END X-axis values, wherein X-START is determined by examining memory data locations (X,Y) where 0≦X≦255 and Y-TOP≦Y≦Y-BOTTOM, by detecting three consecutive columns of whitespace data and a next column having a greylevel value equal to said second predetermined value and considering the memory data location of said next column to be a first part of said fingerprint image data along the X-axis, and wherein X-END is determined in similar manner as for said X-START value but in an opposite direction from 255≧X≧along the X-axis so that said X-END value indicates the memory data location along the X-axis where the fingerprint image data ends; computing the Y-Axis Range of the framed image data to indicate the start and end memory locations of the fingerprint image data on the Y-axis by determining Y-START and Y-END Y-axis values, wherein Y-START is determined by memory data locations (X,Y) where X-START≦X≦X-END and Y-TOP≦Y≦Y-BOTTOM by detecting three consecutive rows of whitespace data and a next row having a greylevel value equal to said second predetermined value and considering the memory data location of said next row to be a first part of said fingerprint image along the Y-axis, and wherein Y-END is determined in similar manner as for said Y-START value but in an opposite direction from Y-BOTTOM≧Y≧Y-TOP along the Y-axis so that said Y-END value indicates the memory data location along the Y-axis where the fingerprint image data ends; defining said fingerprint identity window by determining the dimension of said window around an origin point defined as (XC,YC) wherein: XC=X-END minus (X-END minus X-START)÷3 and YC=Y-END minus (Y-END minus Y-START)÷2; and further defining the dimensional area of the said fingerprint identity window by predetermining a window-size for said fingerprint identity window and defining said dimensional area as from (XC-DIFF, YC-DIFF) to (XC+DIFF, YC+DIFF) where DIFF=1/2(window-size minus 1), wherein (XC-DIFF)=Xs (YC-DIFF)=Ys, (XC+DIFF)=Xe, and (YC+DIFF)=Ye.

Claim 2

A method for the automatic non-minutiae identification of a fingerprint of a person to be identified, comprising the steps of: video scanning an image of a fingerprint and producing fingerprint image data and whitespace data; electronically storing in digital form, in an addressable memory, said fingerprint image data and whitespace data; determining the location of the said fingerprint image data stored in digital form in said addressable memory with the said whitespace data; image framing the said fingerprint image data and whitespace data to a predetermined dimension, and establishing Y-TOP and Y-BOTTOM values along the Y-axis of said predetermined dimension; computing the X-Axis Range of the fingerprint image data contained in the framed image data by determining two X-axis values, said X-axis values being X-START and X-END, wherein X-START indicates the memory data location where the fingerprint image data starts on the X-axis, and X-END indicates the memory data location where the fingerprint image data ends on the X-axis; computing the Y-Axis Range of the fingerprint image data contained in the framed image data by determining two Y-axis values, said Y-axis values being Y-START and Y-END, wherein in Y-START indicates the memory data location where the fingerprint image data starts on the Y-axis, and Y-END indicates the memory data location where the fingerprint image data ends on the Y-axis; determining the dimensional area of said fingerprint image data by utilizing said X-START, X-END, Y-START and Y-END values; defining a fingerprint identity window within said fingerprint image data; defining said whitespace data as having a predetermined greylevel value; defining said fingerprint image data as having a second predetermined greylevel value distinct from that defined for the said whitespace data; as to said image framing, examining memory data locations (128, Y) where 0≦Y≦255, and upon finding three consecutive rows of whitespace data, defining Y-TOP as the latter examined data row Y-axis value, and examining memory data locations (128, Y) where 255≧Y≧0 and upon finding three consecutive rows of whitespace data, defining Y-BOTTOM as the last examined data row Y-axis value; computing the X-Axis Range of the framed image data to indicate the start and end memory locations of the fingerprint image data on the X-axis by determining X-START and X-END X-axis values, wherein X-START is determined by examining memory data locations (X,Y) where 0≦X≦255 and Y-TOP≦Y≦Y-BOTTOM, by detecting three consecutive columns of whitespace data and a next column having a greylevel value equal to said second predetermined value and considering the memory data location of said next column to be a first part of said fingerprint image data along the X-axis, and wherein X-END is determined in similar manner as for said X-START value but in an opposite direction from 255≧X≧along the X-axis so that said X-END value indicates the memory data location along the X-axis where the fingerprint image data ends; computing the Y-Axis Range of the framed image data to indicate the start and end memory locations of the fingerprint image data on the Y-axis by determining Y-START and Y-END Y-axis values, wherein Y-START is determined by memory data locations (X,Y) where X-START≦X≦X-END and Y-TOP≦Y≦Y-BOTTOM by detecting three consecutive rows of whitespace data and a next row having a greylevel value equal to said second predetermined value and considering the memory data location of said next row to be a first part of said fingerprint image along the Y-axis, and wherein Y-END is determined in similar manner as for said Y-START value but in an opposite direction from Y-BOTTOM≧Y≧Y-TOP along the Y-axis so that said Y-END value indicates the memory data location along the Y-axis where the fingerprint image data ends; defining said fingerprint identity window by determining the dimension of said window around an origin point defined as (XC,YC) wherein: XC=X-END minus (X-END minus X-START)÷3 and YC=Y-END minus (Y-END minus Y-START)÷2; and further defining the dimensional area of the said fingerprint identity window by predetermining a window-size for said fingerprint identity window and defining said dimensional area as from (XC-DIFF, YC-DIFF) to (XC+DIFF, YC+DIFF) where DIFF=1/2(window-size minus 1), wherein (XC-DIFF)=Xs (YC-DIFF)=Ys, (XC+DIFF)=Xe, and (YC+DIFF)=Ye.

Claim 3

A method for automatic non-minutiae identification of a fingerprint of a person to be identified, comprising the steps of: video scanning an image of a fingerprint and producing fingerprint image data and whitespace data; electronically storing in digital form in addressable memory, said fingerprint image data and whitespace data; determining the location of the said fingerprint image data stored in digital form in said addressable memory with the said whitespace data; defining a fingerprint identity window within said fingerprint image data stored in the said addressable memory; defining said fingerprint identity window by determining the dimensions of said window around an origin point defined as (XC, YC), wherein XC=X-END minus (X-END minus X-START) divided by 3, and YC=Y-END minus (Y-END minus Y-START). divided by 2; defining the dimensional area of the said fingerprint identity window by predetermining a window-size for said fingerprint identity window and defining said dimensional areas as from (XC-DIFF, YC-DIFF) to (XC+DIFF, YC+DIFF DIFF=1/2(window-size minus 1) and (XC-DIFF)=Xs, (XC+DIFF)=Xe, (YC-DIFF)=Ys, and (YC+DIFF)=Ye; computing a count S1 of ridges contained within a diagonal line from (Xs,Ys) to (Xe,Ye); computing a count S2 of ridges contained within a diagonal line from (Xs,Ye) to (Xe,Ys); computing a count Yma equal to the highest number of ridges found within any horizontal line in the Y-Axis "A-Range" which is defined as: Ys≧horizontal line<YC; computing a count Ymb equal to the highest number of ridges found within any horizontal line in the Y-Axis "B-Range" which is defined as: YC<horizontal line≦Ye; computing a count Ya equal to the sum total number of ridges found within all horizontal lines in the Y-Axis "A-Range" which is defined as: Ys≧horizontal line<YC, wherein Ya is stored as two counts, Yaα and Yaβ, wherein Yaα=total number of ridges on the base 256 horizontal lines in said sum total, and Yaβ=the remaining number or ridges counted which is always a number<256, wherein Ya=(Yaα(256) Yaβ)÷(windowsize ÷2); computing a count Yb equal to the sum total number Of ridges found within all horizontal lines in the Y-Axis "Range" which is defined as: YC<horizontal line≧Ye, wherein Yb is stored as two counts, Ybα and Ybβ, where Ybα=total number of ridges on the base 256 horizontal lines in said sum total, and Ybβ=the remaining number of ridgess counted (window-size÷2); computing a count Yc equal to the number of ridges found within horizontal line YC on the Y-axis, wherein Yc is a whole number and YC is the Y-axis center line of said fingerprint identity window; computing a count Xma equal to the highest number of ridges found within any vertical line in the X-Axis "A-Range" which is defined as: Xs≧vertical line<XC; computing a count Xmb equal to the highest number of ridges found within any vertical line in the X-Axis "B-Range" which is defined as: XC<vertical line≦Xe; computing a count Xa equal to the sum total number of ridges found within all vertical lines in the X-Axis "A-Range" which is defined as: Xs≦vertical line<XC, wherein Xa is stored as two counts, Xaα and Xaβ, wherein Xaα=total number of ridges on the base 256 vertical lines in sum total, and Xaβ=the remaining number of ridges counted which is always a number<256, wherein Xa=(Xaα(256)+Xaβ)÷(window-size÷2); computing a count Xb equal to the sum total number of ridges found within all vertical lines in the X-Axis "B-Range" which is defined as: XC<vertical line≦Xe, wherein Xb is stored as two counts, Xbα and Xbβ, wherein Xb=total number of ridges on the base 256 vertical lines in said sum total, and Xbβ=the remaining number of ridges counted which is always a number<256, wherein Xb=Xbα(256)+Xbβ)÷(window-size÷2); computing a count Xc equal to the number of ridges found within vertical line XC on the X-axis center line of said fingerprint identity window; and compiling a data matrix from said counts S1, S2, Yma, Ymb, Ya, Yb, Yc, Xma, Xmb, Xa, Xb and Xc to provide a non-minutiae digitized numeric identifier having 24 bytes of fingerprint identification data.

Claim 4

A method for automatic non-minutiae identification of a fingerprint of a person to be identified, comprising the steps of: video scanning an image of a fingerprint and producing fingerprint image data and whitespace data; electronically storing in digital form in addressable memory, said fingerprint image data and whitespace data; determining the location of the said fingerprint image data stored in digital form in said addressable memory with the said whitespace data; defining a fingerprint identity window within said fingerprint image data stored in the said addressable memory; defining said fingerprint identity window by determining the dimensions of said window around an origin point defined as (XC, YC), wherein XC=X-END minus (X-END minus X-START) divided by 3, and YC=Y-END minus (Y-END minus Y-START). divided by 2; defining the dimensional area of the said fingerprint identity window by predetermining a window-size for said fingerprint identity window and defining said dimensional areas as from (XC-DIFF, YC-DIFF) to (XC+DIFF, YC+DIFF DIFF=1/2(window-size minus 1) and (XC-DIFF)=Xs, (XC+DIFF)=Xe, (YC-DIFF)=Ys, and (YC+DIFF)=Ye; computing a count S1 of ridges contained within a diagonal line from (Xs,Ys) to (Xe,Ye); computing a count S2 of ridges contained within a diagonal line from (Xs,Ye) to (Xe,Ys); computing a count Yma equal to the highest number of ridges found within any horizontal line in the Y-Axis "A-Range" which is defined as: Ys≧horizontal line<YC; computing a count Ymb equal to the highest number of ridges found within any horizontal line in the Y-Axis "B-Range" which is defined as: YC<horizontal line≦Ye; computing a count Ya equal to the sum total number of ridges found within all horizontal lines in the Y-Axis "A-Range" which is defined as: Ys≧horizontal line<YC, wherein Ya is stored as two counts, Yaα and Yaβ, wherein Yaα=total number of ridges on the base 256 horizontal lines in said sum total, and Yaβ=the remaining number or ridges counted which is always a number<256, wherein Ya=(Yaα(256) Yaβ)÷(windowsize ÷2); computing a count Yb equal to the sum total number Of ridges found within all horizontal lines in the Y-Axis "Range" which is defined as: YC<horizontal line≧Ye, wherein Yb is stored as two counts, Ybα and Ybβ, where Ybα=total number of ridges on the base 256 horizontal lines in said sum total, and Ybβ=the remaining number of ridgess counted (window-size÷2); computing a count Yc equal to the number of ridges found within horizontal line YC on the Y-axis, wherein Yc is a whole number and YC is the Y-axis center line of said fingerprint identity window; computing a count Xma equal to the highest number of ridges found within any vertical line in the X-Axis "A-Range" which is defined as: Xs≧vertical line<XC; computing a count Xmb equal to the highest number of ridges found within any vertical line in the X-Axis "B-Range" which is defined as: XC<vertical line≦Xe; computing a count Xa equal to the sum total number of ridges found within all vertical lines in the X-Axis "A-Range" which is defined as: Xs≦vertical line<XC, wherein Xa is stored as two counts, Xaα and Xaβ, wherein Xaα=total number of ridges on the base 256 vertical lines in sum total, and Xaβ=the remaining number of ridges counted which is always a number<256, wherein Xa=(Xaα(256)+Xaβ)÷(window-size÷2); computing a count Xb equal to the sum total number of ridges found within all vertical lines in the X-Axis "B-Range" which is defined as: XC<vertical line≦Xe, wherein Xb is stored as two counts, Xbα and Xbβ, wherein Xb=total number of ridges on the base 256 vertical lines in said sum total, and Xbβ=the remaining number of ridges counted which is always a number<256, wherein Xb=Xbα(256)+Xbβ)÷(window-size÷2); computing a count Xc equal to the number of ridges found within vertical line XC on the X-axis center line of said fingerprint identity window; and compiling a data matrix from said counts S1, S2, Yma, Ymb, Ya, Yb, Yc, Xma, Xmb, Xa, Xb and Xc to provide a non-minutiae digitized numeric identifier having 24 bytes of fingerprint identification data.