• Title/Summary/Keyword: MMCCD

Search Result 1, Processing Time 0.016 seconds

Image Retrieval Using Spatial Color Correlation and Texture Characteristics Based on Local Fourier Transform (색상의 공간적인 상관관계와 국부적인 푸리에 변환에 기반한 질감 특성을 이용한 영상 검색)

  • Park, Ki-Tae;Moon, Young-Shik
    • Journal of the Institute of Electronics Engineers of Korea SP
    • /
    • v.44 no.1
    • /
    • pp.10-16
    • /
    • 2007
  • In this paper, we propose a technique for retrieving images using spatial color correlation and texture characteristics based on local fourier transform. In order to retrieve images, two new descriptors are proposed. One is a color descriptor which represents spatial color correlation. The other is a descriptor combining the proposed color descriptor with texture descriptor. Since most of existing color descriptors including color correlogram which represent spatial color correlation considered just color distribution between neighborhood pixels, the structural information of neighborhood pixels is not considered. Therefore, a novel color descriptor which simultaneously represents spatial color distribution and structural information is proposed. The proposed color descriptor represents color distribution of Min-Max color pairs calculating color distance between center pixel and neighborhood pixels in a block with 3x3 size. Also, the structural information which indicates directional difference between minimum color and maximum color is simultaneously considered. Then new color descriptor(min-max color correlation descriptor, MMCCD) containing mean and variance values of each directional difference is generated. While the proposed color descriptor includes by far smaller feature vector over color correlogram, the proposed color descriptor improves 2.5 % ${\sim}$ 13.21% precision rate, compared with color correlogram. In addition, we propose a another descriptor which combines the proposed color descriptor and texture characteristics based on local fourier transform. The combined method reduces size of feature vector as well as shows improved results over existing methods.