CANDID: comparison algorithm for navigating digital image databases

In this paper, we propose a method for calculating the similarity between two digital images. A global signature describing the texture, shape, or color content is first computed for every image stored in a database, and a normalized distance between probability density functions of feature vectors is used to match signatures. This method can be used to retrieve images from a database that are similar to an example target image. This algorithm is applied to the problem of search and retrieval for a database containing pulmonary CT imagery, and experimental results are provided.<<ETX>>

[1]  K. Wakimoto,et al.  Efficient and Effective Querying by Image Content , 1994 .

[2]  R. DeMori,et al.  Handbook of pattern recognition and image processing , 1986 .

[3]  Peter E. Hart,et al.  Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.

[4]  Patrick M. Kelly,et al.  An adaptive algorithm for modifying hyperellipsoidal decision surfaces , 1992, [Proceedings 1992] IJCNN International Joint Conference on Neural Networks.

[5]  Peiya Liu,et al.  Content-based indexing technique using relative geometry features , 1992, Electronic Imaging.

[6]  Pasquale Savino,et al.  Automatic Image Indexation to Support Content-Base Retrieval , 1992, Inf. Process. Manag..

[7]  Chin-Chen Chang,et al.  Retrieving the Most Similar Symbolic Pictures from Pictorial Databases , 1992, Inf. Process. Manag..

[8]  Julius T. Tou,et al.  Pattern Recognition Principles , 1974 .

[9]  Roy E. Kimbrell,et al.  Searching for text? Send an N-gram] , 1988 .

[10]  Arun K. Sood,et al.  Comparison of subband features for automatic indexing of scientific image databases , 1994, Electronic Imaging.

[11]  K. Laws.  Textured Image Segmentation , 1980 .

[12]  Richard O. Duda,et al.  Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.

[13]  SUH-YIN LEE,et al.  Spatial reasoning and similarity retrieval of images using 2D C-string knowledge representation , 1992, Pattern Recognit..

[14]  Kenneth I. Laws,et al.  Rapid Texture Identification , 1980, Optics & Photonics.

[15]  Christos Faloutsos,et al.  QBIC project: querying images by content, using color, texture, and shape , 1993, Electronic Imaging.

[16]  Patrick M. Kelly,et al.  Experience with CANDID: comparison algorithm for navigating digital image databases , 1995, Other Conferences.