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

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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 - PowerPoint PPT Presentation

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  • MPEG-7 DCD using Merged Palette Histogram Similarity MeasureLai-Man Po and Ka-Man Wong

    ISIMP 2004Oct 20-22, Poly U, Hong Kong

    Department of Electronic EngineeringCity University of Hong Kong

  • MPEG-7 Dominant Color DescriptorA compact and effective descriptorGenerated by GLA color quantizationMaximum of 8 colors in storage

  • Dominant Color DescriptorSimilarity measureA 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.

  • DCD-QHDM upper bound problemLimitations of QHDM - 1Distance upper bound is varied by number of matching colorsCompletely different image cannot be identified by its upper bound

  • DCD-QHDM upper bound problemAnalysis of problem 1The upper-bound of the distance measured varies by number of color in the descriptor

    Maximum of positive part is not a constantMaximum of negative part is zeroSo, the maximum of QHDM result is not fixedThis property makes DCD unable to identify completely different images by the values measuredPositive partNegative part

  • DCD-QHDM Similarity coefficient problemLimitations of QHDM - 2The similarity coefficient does not well model color similarityIt does not balance between color distance and area of matching

  • DCD-QHDM Similarity coefficient problemThe similarity coefficient use the color distance to fine tune the similarityDifficult 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.)

  • Proposed Merged Palette Histogram Similarity MeasureMPHSM Process - 1Find the closest pair of colors using Euclidian distance in CIELuv color space

    MPHSM process - 2If the distance smaller than a threshold Td, merge them to form a new common palette color

  • Proposed Merged Palette Histogram Similarity MeasureMPHSM process - 3A new common palette is then generatedForm new descriptors based on the common palette

  • Proposed Merged Palette Histogram Similarity MeasureMPHSM process - 4Histogram intersection is used to measure the similarityCount the non-overlapping area as the distance

  • Flow of MPHSM

  • Experiment Result of MPH-RFExperiment MethodologyANMRR

    Image Database5466 Images from MPEG-7 common color dataset (CCD)50 Pre-defined query and ground truth sets

  • Latest experimental resultsMPHSM without spatial coherence improves DCD by about 0.04 of ANMRR in average Very close to QHDM with spatial coherenceSignificant improve in medium queriesIt gives significant improvement on visual results

    *ANMRR (smaller means better)

  • Experimental resultsVisual results - Query #32 from MPEG-7 CCDDemo available in http://www.ee.cityu.edu.hk/~mirror/

    Query imageQHDM results, ANMRR=0.4MPHSM result, ANMRR=0.0111

  • Experimental resultsVisual results - Query #25 from MPEG-7 CCDDemo available in http://www.ee.cityu.edu.hk/~mirror/

    Query imageQHDM results, ANMRR=0.3935MPHSM result, ANMRR=0.0481

  • ConclusionA 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 match identical colors as well as similar colors

    Use area of matching for similarity measure

  • ConclusionExperimental 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.