Part II HistogramRepresentation of Color Feature in Image

Part II: Histogram—Representation of Color Feature in Image Processing Yang, Li

Structure: • Color histogram descriptor • Color cooccurrence histogram • HSV space segmentation

• Color histogram descriptor <C, M, { Ci}, {H( Ci)}> • A weighted Euclidean distance of colors is then taken to match color histograms, if X is the query histogram and Y is the histogram of an item in the database, then the similarity between X and Y is given by: ||Z||=Z'AZ

Region-Color Descriptor • The region information in both query and image can be represented using the region color descriptor with the difference that the number of regions and their respective colors are different. • For a set of image regions though, the color label or indes assigned to the corresponding regions must be the same.

Color Cooccurrence Histogram • Each model image is represented as a color CH. • The color CH holds the number of occurrences of pairs of color pixels C 1=(R 1, G 1, B 1) and C 2=(R 2, G 2, B 2) separated by a vector in the image C 2 y plane( x, y). y C 1 x

Assumption: ignore the direction of( x, y) and keep track of only magnitude d= • Quantize colors into a set of representative colors C=(c 1, c 2, …, c ) • Quantize the distances into a set of distance ranges D={[0, 1), [1, 2), …, [ -1, )}. • CH is represented by CH (i, j, k).

The image and model CHs are compared by computing their intersection. The intersection is: It indicates how well the image CH accounts for the model CH.

Recursive HSV-space segmentation to extract regions within the image which contain perceptually similar color The conversion form RGB to HSV is performed with the equations: Where H=H 1 if B<=G; otherwise H=360 -H 1;

If the colors with value<25%, they are classified as black; if the color with saturation<20% and value>75%, they can be classified as white VAL Green 120 Blue 240 Yellow 60 Magenta 300 BRIGHT CHROMATIC black hue SAT

White Black yes no Value>75 IMAGE SAT<20 Value<25 no no Value>75 SAT>=20 bright chromatic yes chromatic Build Hue Build Saturation Histogram Determine N peaks M peaks Threshhold Peak i Peak j no i=n? no i=m ? yes END