Content-based image retrieval apparatus and method via relevance feedback by using fuzzy integral

A content-based image retrieval method via relevance feedback by using fuzzy integral, comprising:

• measuring similarities according to feature between images stored in a database and a new query image;
• associating the similarities measured according to feature by using the fuzzy integral to measure similarities according to the fuzzy integral;
• bringing images sequentially in the order of higher similarity according to the finally obtained similarities and transmitting a search result;
• and
• recalculating similarities according to feature via relevance feedback about the query result to output converted images
• wherein the final image similarities are measured based on an equation as:
• Cg(S, i, j)=k=1 , . . . , n[S(k)(xi(k), xj(k))−S(k−1)(xi(k−1), xj(k−1))g(A(k))]
• where S={s1, . . . , sn} is a set of similarity measurement functions between two images, X={x1, . . . xn} is a set of image features, xi(k) and xj(k) are kth image features of query images i and j, n is a total number of used image features, g(A(k)), which is also expressed as gk, denotes relevance of a feature subset A(k)={x(1), . . . , x(k)}, and 0≦s(1)(xi(1), xj(1))≦ . . . ≦s(n)(xi(n), xj(n))≦1.

A computer readable record medium storing instructions for executing a content-based image retrieval method, comprising:

• measuring similarities according to feature between images stored in a database and a new query image;
• associating the similarities measured according to feature by using the fuzzy integral to measure similarities according to the fuzzy integral;
• bringing images sequentially in the order of higher similarity according to the finally obtained similarities and transmitting a search result;
• and
• recalculating similarities according to feature via relevance feedback about the query result to output converted images
• wherein the final image similarities are measured based on an equation as:
• Cg(S, i, j)=k=1 , . . . , n[S(k)(xi(k), xj(k))−S(k−1)(xi(k−1), xj(k−1))g(A(k))]
• where S={s1, . . . sn} is a set of similarity measurement functions between two images, X={x1, . . . xn} is a set of image features, xi(k) and xi(k) are kth image features of query images i and j, n is the total number of the used image features, g(A(k)), which is also expressed as gk, denotes relevance of a feature subset A(k)={x(1), . . . x(k)} and 0≦s(1)(xi(1), xj(1))≦ . . . ≦s(n)(xi(n), xj(n))≦1.