Nearly a year ago, I started developing a program that would automatically identify ranked peaks. It uses the USGS National Elevation Dataset (NED), which is very similar to what we see on the USGS topo maps. I used the 1-arc-second data (~30 m horizontal resolution) and have just finished processing the entire country (minus Alaska). The program identifies any peaks that are either ranked, or nearly ranked. Then, it checks to see if there is a LOJ ranked (or soft ranked) peak within 100 meters. If there is not a ranked peak on LOJ, it outputs the information for this ranked peak candidate. I also designed it to verify the peak prominences of all LOJ peaks.
In the meantime, John Kirk has been doing the VERY tedious task of looking at the thousand and thousands of ranked peak candidates, and verifying on topo maps which are indeed ranked (or soft ranked). I'm guessing only 10% of the candidates actually end up making it (John, you might have a better estimate), because of a multitude of factors, including: summit is nearly ranked, another nearby topmost closed contours of the same elevation, large summit plateaus where the high point is off to one side, variations between NED and topo maps, etc.
Thus far, John has inspected about 3/4ers of the country and has added 744 ranked peaks and 1055 soft ranked peaks! Considering that John (and a few others) had already identified nearly 88,000 ranked peaks, this is only a slight increase in the total number. It is also a testament to John's diligence, that he had already identified nearly 99% of all the ranked peaks.
I wrote the program in FORTRAN 90 and NCL (a meteorology-centric language). If anyone else wants to use it for another country or region, I am happy to share it, as long as you give me and LOJ credit. However, you will need to be a relatively knowledgeable programmer to adapt it to other areas; though, I have designed it to be rather flexible and could help you set it up.