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MPEG-7 DCD using Merged Palette Histogram Similarity Measure

MPEG-7 DCD using Merged Palette Histogram Similarity Measure. Lai-Man Po and Ka-Man Wong ISIMP 2004 Oct 20-22, Poly U, Hong Kong Department of Electronic Engineering City University of Hong Kong. A compact and effective descriptor Generated by GLA color quantization

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MPEG-7 DCD using Merged Palette Histogram Similarity Measure

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  1. MPEG-7 DCD using Merged Palette Histogram Similarity Measure Lai-Man Po and Ka-Man Wong ISIMP 2004 Oct 20-22, Poly U, Hong Kong Department of Electronic Engineering City University of Hong Kong

  2. A compact and effective descriptor Generated by GLA color quantization Maximum of 8 colors in storage MPEG-7 Dominant Color Descriptor

  3. Percentage p color Percentage q color Dominant Color Descriptor • Similarity measure • A modified Quadratic Histogram Distance Measure (QHDM) • Since each DCD may have different set of colors, QHDM is used to account for identical colors and similar colors.

  4. F 1/3 3 I I I I 2 3 1 1 1/2 1/2 1/2 F F F 2 1 1 DCD-QHDM upper bound problem • Limitations of QHDM - 1 • Distance upper bound is varied by number of matching colors • Completely different image cannot be identified by its upper bound

  5. DCD-QHDM upper bound problem • Analysis of problem 1 • The upper-bound of the distance measured varies by number of color in the descriptor • Maximum of positive part is not a constant • Maximum of negative part is zero • So, the maximum of QHDM result is not fixed • This property makes DCD unable to identify completely different images by the values measured Positive part Negative part

  6. I I I I 2 1 1 4 1 1/2 1/2 1/2 F F F F 2 1 1 4 DCD-QHDM Similarity coefficient problem • Limitations of QHDM - 2 • The similarity coefficient does not well model color similarity • It does not balance between color distance and area of matching

  7. T d d a = 1.2 a = 44% a = 16.67% a = 0% DCD-QHDM Similarity coefficient problem • The similarity coefficient use the color distance to fine tune the similarity • Difficult to define a quantitative similarity between colors, • Sensitivity of human eye depends on many conditions (e.g. light source of the room, spatial layout of the image, etc.)

  8. Common Palette Proposed Merged Palette Histogram Similarity Measure • MPHSM Process - 1 • Find the closest pair of colors using Euclidian distance in CIELuv color space • MPHSM process - 2 • If the distance smaller than a threshold Td, merge them to form a new common palette color

  9. Common Palette Merged Palette Histogram Dominant Color Descriptor Proposed Merged Palette Histogram Similarity Measure • MPHSM process - 3 • A new common palette is then generated • Form new descriptors based on the common palette

  10. Proposed Merged Palette Histogram Similarity Measure • MPHSM process - 4 • Histogram intersection is used to measure the similarity • Count the non-overlapping area as the distance

  11. Initial DCDs Step 1: Find a pair of colors with minimum distance d d<Td ? Step2: Merge colors having minimum distance Y N Common Palette Step 3: Update each DCD based on the common palette Step 4: Histogram Intersection Flow of MPHSM

  12. Experiment Result of MPH-RF • Experiment Methodology • ANMRR • Image Database • 5466 Images from MPEG-7 common color dataset (CCD) • 50 Pre-defined query and ground truth sets

  13. Latest experimental results • MPHSM without spatial coherence improves DCD by about 0.04 of ANMRR in average • Very close to QHDM with spatial coherence • Significant improve in medium queries • It gives significant improvement on visual results *ANMRR (smaller means better)

  14. Experimental results • Visual results - Query #32 from MPEG-7 CCD • Demo available in http://www.ee.cityu.edu.hk/~mirror/ Query image QHDM results, ANMRR=0.4 MPHSM result, ANMRR=0.0111

  15. Experimental results • Visual results - Query #25 from MPEG-7 CCD • Demo available in http://www.ee.cityu.edu.hk/~mirror/ Query image QHDM results, ANMRR=0.3935 MPHSM result, ANMRR=0.0481

  16. Conclusion • A new merged palette histogram similarity measure for dominant color descriptor of MPEG-7 is proposed • The merged palette formed a common color space and used to redefine the new query histograms for histogram intersection similarity measure. • Can matchidentical colors as well as similar colors • Use area of matching for similarity measure

  17. Conclusion • Experimental results show that the proposed MPHSM improve DCD-QHDM using ANMRR rating by about 0.04 and very close to the result of DCD-QHDM with spatial coherence • Our experiment result also found that the result of proposed method can be further improved by spatial coherence • The proposed method also provide better perceptually relevant image retrieval.

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