Apparatus for determining ridge direction patterns

Claim 1

An apparatus for determining ridge direction patterns comprising: an image memory for storing data f(x,y) of an image of a pixel at a coordinates position (x,y) in a picture of a skin surface at a memory address corresponding to said coordinates position (x,y); means for calculating gradient vectors from data stored in said image memory, X-component and Y-component of said gradient vector at a position (x,y) being αf(x,y)/αx and αf(x,y)/αy respectively; gradient vector memory for storing calculated gradient vectors at memory address corresponding to said position (x,y); and means for analyzing distributions of gradient vectors, wherein a direction perpendicular to a principal axis of said distribution is determined as a ridge direction of a subregion, wherein: said means for analyzing distributions of gradient vectors calculates said direction of said principal axis of said distribution of said subregion by a multiple regression analysis in which an energy function E(a,b) is defined by E(a,b)=Σ∥q i -(ap i +b)∥ 2 where p i and q i respectively represent αf(x,y)/αx and αf(x, y)/αy at point i in a subregion and Σ represents summation for all points i in said subregion; values of variables a,b which minimize said energy function are obtained; and from the value of `a`, said ridge direction of said subregion is determined.

Claim 2

An apparatus for determining ridge direction patterns comprising: an image memory for storing data f(x,y) of an image of a pixel at a coordinates position (x,y) in a picture of a skin surface at a memory address corresponding to said coordinates position (x,y); means for calculating gradient vectors from data stored in said image memory, X-component and Y-component of said gradient vector at a position (x,y) being αf(x,y)/αx and αf(x,y)/αy respectively; gradient vector memory for storing calculated gradient vectors at memory address corresponding to said position (x,y); and means for analyzing distributions of gradient vectors, wherein a direction perpendicular to a principal axis of said distribution is determined as a ridge direction of a subregion, wherein: said means for analyzing distributions of gradient vectors calculates said direction of said principal axis of said distribution of said subregion by a multiple regression analysis in which an energy function E(a,b) is defined by E(a,b)=Σ∥q i -(ap i +b)∥ 2 where p i and q i respectively represent αf(x,y)/αx and αf(x, y)/αy at point i in a subregion and Σ represents summation for all points i in said subregion; values of variables a,b which minimize said energy function are obtained; and from the value of `a`, said ridge direction of said subregion is determined.

Claim 3

An apparatus for determining ridge direction patterns comprising: an image memory for storing data f(x,y) of an image of a pixel at a coordinates position (x,y) in a picture of a skin surface at a memory address corresponding to said coordinates position (x,y); means for calculating gradient vectors from data stored in said image memory, X-component and Y-component of said gradient vector at a position (x,y) being αf(x,y)/αx and αf(x,y)/αy respectively; gradient vector memory for storing calculated gradient vectors at memory address corresponding to said position (x,y); and means for analyzing distributions of gradient vectors, wherein a direction perpendicular to a principal axis of said distribution is determined as a ridge direction of a subregion, wherein: said means for analyzing distributions of gradient vectors calculates said direction by a principal component analysis in which variance-covariance matrix of gradient vectors in said subregion is determined; eigenvalues λ 1 , λ 2 , (λ 1 >λ 2 ) and eigenvectors e 1 , e 2 are determined from said matrix; and from the eigenvalues and eigenvectors, said ridge direction of said subregion is determined.

Claim 4

An apparatus for determining ridge direction patterns comprising: an image memory for storing data f(x,y) of an image of a pixel at a coordinates position (x,y) in a picture of a skin surface at a memory address corresponding to said coordinates position (x,y); means for calculating gradient vectors from data stored in said image memory, X-component and Y-component of said gradient vector at a position (x,y) being αf(x,y)/αx and αf(x,y)/αy respectively; gradient vector memory for storing calculated gradient vectors at memory address corresponding to said position (x,y); and means for analyzing distributions of gradient vectors, wherein a direction perpendicular to a principal axis of said distribution is determined as a ridge direction of a subregion, wherein: said means for analyzing distributions of gradient vectors calculates said direction by a principal component analysis in which variance-covariance matrix of gradient vectors in said subregion is determined; eigenvalues λ 1 , λ 2 , (λ 1 >λ 2 ) and eigenvectors e 1 , e 2 are determined from said matrix; and from the eigenvalues and eigenvectors, said ridge direction of said subregion is determined.