Ground truth generation for image segmentation

A system comprising one or more processors for executing computer-readable instructions, the computer-readable instructions controlling the one or more processors to perform operations comprising:

• providing a set of input documents of a first format, each of the set of input documents comprising one or more document pages;
• splitting the input documents into its individual document pages;
• parsing the individual document pages of the first format, the parsing comprising identifying a predefined set of items including position information of the position of the predefined set of items in the individual document pages;
• generating a bitmap image of a second format for each individual document page of the first format, the bitmap image comprising a predefined number of pixels;
• generating a mask for each individual document page, the mask comprising the predefined number of pixels of the corresponding bitmap image;
• and
• assigning an encoded class label to each pixel of the mask based on the position information of identified items of the predefined set of items.

A computer program product comprising a computer-readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to perform operations comprising:

• providing a set of input documents of a first format, each of the input documents comprising one or more document pages;
• splitting the input documents into individual document pages;
• parsing the individual document pages of the first format, the parsing comprising identifying a predefined set of items including position information of the position of the predefined set of items in the individual document pages;
• generating a bitmap image of a second format for each individual document page of the first format, the bitmap image comprising a predefined number of pixels;
• generating a mask for each individual document page, the mask comprising the predefined number of pixels of the corresponding bitmap image;
• and
• assigning an encoded class label to each pixel of the mask based on the position information of identified items of the predefined set of items.

A method comprising:

• receiving a training data set, the training data set comprising:
• a plurality of individual document pages of a first format;
• a bitmap image of a second format for each of the plurality of individual document pages of the first format, the bitmap comprising a predefined number of pixels;
• a mask for each of the plurality of individual document pages of the first format, the mask comprising the predefined number of pixels of the corresponding bitmap image;
• and
• an encoded class label assigned to each pixel of the mask based on position information of identified items of the predefined set of items;
• and
• training a cognitive model of an image segmentation application with the training data set.

A cognitive model, the cognitive model being encoded on a non-transitory computer readable medium, the cognitive model comprising:

• a training data set, the training data set comprising:
• a plurality of individual document pages of a first format;
• a bitmap image of a second format for each of the plurality of individual document pages of the first format, the bitmap comprising a predefined number of pixels;
• a mask for each of the plurality of individual document pages of the first format, the mask comprising the predefined number of pixels of the corresponding bitmap image;
• and
• an encoded class label assigned to each pixel of the mask based on position information of identified items of the predefined set of items.