Figure 1
Here we have four variants of the same text being compared. Through the software, users can select their points of interest in the variants which are represented by the rectagles on each image. The result of stacking the images one upon the other is then displayed in the lower half of the screen, and users can select from the available variants what combination of layers they would like to view.
Figure 2
This figure is a sample product of the layering process. Where the variants are exactly the same, the text comes through as clear and legible. Where variations occur, however, the software renders the differences as blurs in the text. Notice the visible blur at the end of the second line of the first stanza.
This figure is a sample product of the layering process. Where the variants are exactly the same, the text comes through as clear and legible. Where variations occur, however, the software renders the differences as blurs in the text. Notice the visible blur at the end of the second line of the first stanza.
Figure 3
This figure demonstrates the program's ability to purposefully deform a curved image to an acceptable standard, and by doing so allows the users to handle images that are not necessarily scanned to a predetermined standard. The process allows for variances due to lighting or even page curvature. The crosshairs represent anchor points within the text around which the standardization process will take place.
This figure demonstrates the program's ability to purposefully deform a curved image to an acceptable standard, and by doing so allows the users to handle images that are not necessarily scanned to a predetermined standard. The process allows for variances due to lighting or even page curvature. The crosshairs represent anchor points within the text around which the standardization process will take place.
Figures 4 and 5
These figures demonstrate early steps in the process of retrieving ( x,y ) coordinates for any given image. The original full-color image is transformed into a noise-reduced black and white image.
These figures demonstrate early steps in the process of retrieving ( x,y ) coordinates for any given image. The original full-color image is transformed into a noise-reduced black and white image.
Figure 4
Figure 5
