| 摘要 |
The present invention aims to provide a method of compiling and retrieving an image database having excellent space efficiency, wherein an associative data structure is used in order to solve the foregoing problem. There is provided a method including the steps of: an extracting step for extracting a plurality of feature vectors from an image formed by capturing an object to be stored into an image database, an n bit of identifier (n is a natural number) being previously assigned to the object and each feature vector representing a local feature of the image, and a storing step for storing each feature vector into the image database using a set of data structures, each data structure admitting a false positive in compensation for reduced memory amount and returning a value showing whether specified data is stored to the data structure or not, so that the identifier of the object is associated with the feature vector extracted therefrom, wherein the set of data structures has at least 2 by n identifier data structures, each identifier data structure corresponding to zero value and one value of each bit of the identifier, the storing step stores each feature vector into the identifier data structures of either zero value or one value of each bit according to the object from which the feature vector is extracted, the image database is accessed by a computer to execute, when an image showing an object is given as a query, a recognition process that examines whether the same object as the query is stored in the image database or not, wherein the recognition process includes steps of: extracting a plurality of feature vectors as query vectors from the query, testing whether the corresponding feature vector to each query vector is stored in the identifier data structures or not, and in case where the corresponding feature vector is stored in either zero value or one value of every bit of the identifier data structures, finding an identifier that relates to the query vector according to a stored value of each bit, so that the query is associated with the most strongly related identifier based on the sum of the tests on each query vector. |
