Image Retrieval System Based on Density Slicing of Colour Histogram of Images Subareas and Colour Pair Segmentation

Techniques to identify objects within an image and searching for similar objects in the database is not claiming a lot of progress, due to the limitations of the capabilities of the existing techniques and algorithms in image processing and computer vision to perform such task. In this paper, a new technique based on slicing the images to equally sub-areas, then applying the density slicing to the colour histogram of these areas combined with the colour pair technique is presented. We tried to overcome problems related to the original colour pair segmentation, as well as overcome problems related to the computational complexity in histogram localization through proposing density slicing or multiple thresholds. In this paper, new techniques proposed, new ranking formula, and a complete framework with the interface consideration.

[1]  Dragutin Petkovic,et al.  Content-Based Representation and Retrieval of Visual Media: A State-of-the-Art Review , 1996 .

[2]  John P. Eakins,et al.  Automatic image content retrieval - are we getting anywhere? , 2002 .

[3]  NagasakaAkio,et al.  Automatic video indexing and full-video search for object appearances (abstract) , 1992 .

[4]  Sethuraman Panchanathan,et al.  Review of Image and Video Indexing Techniques , 1997, J. Vis. Commun. Image Represent..

[5]  Tat-Seng Chua,et al.  Content-based retrieval of segmented images , 1994, MULTIMEDIA '94.

[6]  Yihong Gong,et al.  An image database system with content capturing and fast image indexing abilities , 1994, 1994 Proceedings of IEEE International Conference on Multimedia Computing and Systems.

[7]  James Lee Hafner,et al.  Efficient Color Histogram Indexing for Quadratic Form Distance Functions , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  Peter G. B. Enser Pictorial information retrieval , 1995 .

[9]  Azriel Rosenfeld,et al.  Computer vision and image processing , 1992 .

[10]  Marcel Worring,et al.  Content-Based Image Retrieval at the End of the Early Years , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  Akio Nagasaka,et al.  Automatic Video Indexing and Full-Video Search for Object Appearances , 1991, VDB.

[12]  Tim Morris,et al.  Computer Vision and Image Processing: 4th International Conference, CVIP 2019, Jaipur, India, September 27–29, 2019, Revised Selected Papers, Part I , 2020, CVIP.