Idext

Idext is a simple tool to extract tabular data from images. Specifically, data is obtained from segments of images provided in a user-given directory. The width and height of segments can be changed. And from each segment the following data is obtained:

• image_no: id of image that the segment is obtained from
• pixel_count: pixel count in the segment (width * height)
• row: row position of the segment in the image
• column: column position of the segment in the image
• vedge_mean, vedge_sd: mean and standard deviation of contrast between vertically adjacent pixels
• hedge_mean, hedge_sd: mean and standard deviation of contrast between horizontally adjacent pixels
• intensity_mean: average of color intensity over all pixels of the segment
• rawred_mean, rawgreen_mean, rawblue_mean: mean of color values
• exred_mean, exgreen_mean, exblue_mean: average of excess color values (exred = 2 red - green - blue)
• hue_mean, saturation_mean, value_mean: average color of pixels in hue, saturation, value space

Each segment can also be assigned a class. For each data-image (image from which data is extracted), user is allowed to supply an additional class-image to characterize classes in the data-image. User can prepare class-images by painting the parts corresponding to classes in the images in red, green, blue, black, or white. Idext understands these colors and assigns classes to segments based on these colors.

Example

Suppose we have a list of images in images folder from which we want to extract some data.

We can identify certain classes in these images by painting paths with red, grass with green and trees with blue color. We put these class-images in classimages folder. Assume, we would like to divide images into segments of 10x10 size. With the following code we can extract tabular data with columns separated by comma in a file called datafile.txt.

require "idext"

def extract_data
    dir = "images"
    cdir = "classimages"
    segment_width = 10
    segment_height = 10
    data_separator = ","
    output_filename = "datafile.txt"
    with_column_names = true
    Idext.extract_data_from_images(dir, cdir,
                                   segment_width, segment_height,
                                   data_separator,
                                   output_filename, with_column_names)

end

extract_data()