Edge Histogram Descriptor

The EHD basically represents the distribution of 5 types of

edges in each local area called a sub-image. As shown in Fig. 1,

螢幕快照 2016-05-27 下午1.53.58

the sub-image is defined by dividing the image space into 4×4

nonoverlapping blocks. Thus, the image partition always yields

16 equal-sized sub-images regardless of the size of the original

image. To characterize the sub-image, we then generate a his-
togram of edge distribution for each sub-image. Edges in the

sub-images are categorized into 5 types: vertical, horizontal,

45-degree diagonal, 135-degree diagonal, and non-directional

edges (Fig. 2).

螢幕快照 2016-05-27 下午1.54.06

Thus, the histogram for each sub-image repre-
sents the relative frequency of occurrence of the 5 types of

edges in the corresponding sub-image. As a result, as shown in

Fig. 3,

螢幕快照 2016-05-27 下午1.54.15

each local histogram contains 5 bins. Each bin corre-
sponds to one of 5 edge types. Since there are 16 sub-images in

the image, a total of 5×16=80 histogram bins is required, (Fig.


螢幕快照 2016-05-27 下午1.54.21

Note that each of the 80-histogram bins has its own seman-
tics in terms of location and edge type. For example, the bin for

the horizontal type edge in the sub-image located at (0,0) in Fig.

1 carries the information of the relative population of the hori-
zontal edges in the top-left local region of the image.

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