segment: Image Segmentation Dataset.

Description Usage Format Source

Description

The instances were drawn randomly from a database of 7 outdoor images. The images were hand segmented to create a classification for every pixel. Each instance is a 3x3 region.

Usage

1

Format

A data frame with 2310 rows and 19 variables:

region-centroid-col

the column of the center pixel of the region.

region-centroid-row

the row of the center pixel of the region.

region-pixel-count

the number of pixels in a region = 9.

short-line-density-5

the results of a line extractoin algorithm that counts how many lines of length 5 (any orientation) with low contrast, less than or equal to 5, go through the region.

short-line-density-2

same as short-line-density-5 but counts lines of high contrast, greater than 5.

vedge-mean

measure the contrast of horizontally adjacent pixels in the region. There are 6, the mean and standard deviation are given. This attribute is used as a vertical edge detector.

vegde-sd

measure the contrast of horizontally adjacent pixels in the region. There are 6, the mean and standard deviation are given. This attribute is used as a vertical edge detector.

hedge-mean

measures the contrast of vertically adjacent pixels. Used for horizontal line detection.

hedge-sd

measures the contrast of vertically adjacent pixels. Used for horizontal line detection.

intensity-mean

the average over the region of (R + G + B)/3.

rawred-mean

the average over the region of the R value.

rawblue-mean

the average over the region of the B value.

rawgreen-mean

the average over the region of the G value.

exred-mean

measure the excess red: (2R - (G + B)).

exblue-mean

measure the excess blue: (2B - (G + R)).

exgreen-mean

measure the excess green: (2G - (R + B)).

value-mean

3-d nonlinear transformation of RGB. (Algorithm can be found in Foley and VanDam, Fundamentals of Interactive Computer Graphics).

saturatoin-mean

3-d nonlinear transformation of RGB. (Algorithm can be found in Foley and VanDam, Fundamentals of Interactive Computer Graphics).

hue-mean

3-d nonlinear transformation of RGB. (Algorithm can be found in Foley and VanDam, Fundamentals of Interactive Computer Graphics).

Source

http://archive.ics.uci.edu/ml/datasets/image+segmentation


hhcartr documentation built on July 2, 2021, 9:06 a.m.