GREENSTONE DIGITAL LIBRARY FROM PAPER TO COLLECTION
Chapter 3 OCR: Optical Character Recognition
An optical character recognition or OCR system transforms a scanned image into text. The input is a digitized image in TIFF or Bitmap format—preferably a clean, high-quality image. The output is a word-processor or web file, typically in RTF, Word, or HTML format.
The following steps are involved in converting paper documents to computer form:
Following these, you must perform quality checks on the resulting files, and save them in the appropriate format.
On the market are many good OCR programs, with prices ranging from $100 to $400.For example, among many others are:
All information, including lists of local distributors, can be found on the manufacturers' websites. Among these, in the authors' experience the most user-friendly are Fine-Reader and Omnipage. Fine-Reader is cheapest, costing about $100. It offers a great deal of flexibility, and the widest range of different language options.
A choice must be made between undertaking the scanning and OCR in-house or outsourcing it to a commercial organization. To do it in-house requires a scanner, OCR software program, OCR skill development, and a quality-conscious, highly motivated workforce.
3.1 The OCR process
The OCR process differs from one OCR program to another, and each one requires a considerable amount of learning. The program's manual will explain this process in detail. Four points deserve particular attention: quality control, tables, images, and specialized material such as formulas, foreign characters etc.
We cannot place enough emphasis on quality control. Quality checks are best performed by native speakers, or people with an excellent command of the language to check. The best people are at the university or high-school level. We should also note that young people tend to sustain higher concentration than older people for this kind of work.
Normally there are four quality checks.
The first is performed at the same time as OCR. Every OCR program has a built-in spell-checker that highlights every suspect letter. At the same time the image of the word appears too, making it easy to check and correct the error.
The second is a general check of the text once the OCR process is finished. Common errors are to miss a page, a paragraph, chapter titles, and so on. A general overview is necessary to check if pages are missing. It is essential to check titles, chapter headings, paragraphs, and tables.
The third is a spelling check using Microsoft Word. This program has a dictionary that is often more sophisticated than the one embedded in OCR programs. By importing the book into Word and performing a spelling check there, more errors can be found and corrected. Be sure to add to the spell-checker any particularly difficult or error-prone words, or scientific and technical terms common in that type of publication.
Finally, the completed document should be checked by an independent person who samples the complete book and checks for errors, problems with tables and images, tagging, and the general look of the resulting text. Only after this final check can a book be considered ready for digital dissemination.
OCR programs do not cope well with tables. Moreover, tables are hard to check. They contain many digits, sometimes with points and commas, and entries are easily misplaced into the wrong row or column. They require concentrated effort, dedicated work, intensive proof-reading, careful checking, and good quality control. They can be handled in three basically different ways.
First, tables can be treated as images. This involves scanning them as black-and-white images and placing them in this form at the appropriate point in the document. This is the easiest solution. There are no errors, and the only time taken is that involved in creating the image. However, this solution consumes more memory than others. Also, the resolution is not always sufficient when large tables are displayed on a computer screen. If you make the complete table fit, the resolution is too small. If you make the table over-wide, the user must scroll to see all columns and rows, and cannot get an overview of the contents.
Second, tables can be recreated manually by making a table with the same number of rows and columns and filling the entries by typing them in, character by character.
Third, the table can be OCR'd. This saves time compared to the manual process, but has a potential for more errors. Columns sometimes get merged, and commas and points are not recognized.
Publications contain three different general types of image:
Black and white line art should be scanned in line art mode and saved as GIF or PNG files. Black and white photographs should be scanned in greyscale mode and saved as GIF or JPEG files. Color photographs should be scanned in color mode and saved as JPEG files. Generally speaking, medium-quality JPEG provides adequate resolution.
For most collections, images consume the bulk of the space required on a hard-disk or CD-ROM. This makes it important to optimize each image for clarity and visibility, while minimizing its size. To save space you might drop some or all of the images if they are not relevant to the text.
Images should be scanned separately, one by one. We recommend giving the image files a name that consists of the first five or six characters used to denote the document followed by the number of the page on which the image was found. An alternative, assuming each document is in its own directory, is to simply use the letter p followed by the page containing the image. If there are several images on a single page, append an additional letter a, b, c… to the filename. For example, if a JPEG image appeared on page 36 of the publication u7548e discussed earlier, it would be placed in a file named u7548e36.jpg or p36.jpg.
Once the images have been scanned, you can put batch-processing programs to work to resize or enhance all the images at once.
Many documents contain specialized material such as special characters, formulas, and difficult pages. Special characters generally relate to different languages and diacritical marks. The language option for the OCR program should be set for the specific language being read. Formulas will have to be recreated manually. Sometimes this is not possible in the OCR program, but only in a word processor like MICROSOFT Word. Difficult pages that contain complex material or are damaged so that a clear image cannot be obtained might have to be retyped manually.
3.2 Productivity and resources
As mentioned earlier, you should not underestimate the difficulty of OCR. Although the economic and practical options for OCR should be considered separately from scanning, similar points arise: the necessary investment in computers; the availability of human resources and management skills; training the workforce; salary costs; the total number of pages to be processed; and whether documents can be outsourced to third parties.
In this section we share our experience of OCR operations in Belgium, Romania and India. All case studies, calculations and figures assume average situations, documents of standard difficulty (including tables and images) such as are found in most archives or libraries, very high-quality results, and a medium- to long-term operation.
OCR is difficult. It demands great concentration and much skill. Before attaining peak productivity level and quality, a learning period of about six weeks is needed.
Typically, best results and productivity are achieved during the first hours of each day. After three hours of OCR work, productivity declines very rapidly, perhaps to 50% of the initial level. After six hours most people become very tired.
The same kind of evolution occurs over the initial weeks. In the first few weeks everyone achieves fairly high productivity, but after that up to two-thirds of people become bored and frustrated. These people either quit or perform poorly in terms of quality and productivity. Even those who pass the first three to five critical weeks and become part of the regular work team often leave in search of a better position after 6 to 12 months.
The remarks made in Section 3.1 about personnel apply particularly to intensive OCR. Quality checks are best undertaken by native speakers or people with a good command of the language being checked. Young people generally sustain higher concentration than older people for OCR work. As a rule-of-the-thumb, people aged between 18 and 23 years tend to be better suited than those over 25.
Finally, OCR can be a boring job, which makes motivation and sustained commitment to quality exceptionally important.
These facts about OCR lead to the following guidelines:
Table 2 OCR productivity
Table 2 gives typical OCR productivity figures. Documents come in all sizes and qualities, and these figures assume that the mix of documents contains an average number of images or tables—say one image and one table of five rows by five columns every 8 pages. They also assume that the page images are of medium to high quality—note that, as discussed above, this depends on the quality of scanning—and that the OCR workers have a good command of the language.
Table 2 gives separate figures for people undergoing training and for those who have reached their optimal productivity level. If a member of the administrative staff were to allocate three hours a day to OCR, they could achieve 180 to 200 pages OCR per month. For full-time staff with proper training, high concentration and dedication to quality, 500 to 600 pages a month can be achieved.
However, the rates that are achieved on difficult pages of low quality, with many columns or many tables, are far lower—perhaps 300 to 400 pages per month for full-time work.
Assume that the salary cost for dedicated and motivated full-time OCR workers is $400 per month, and the overhead—including management costs, computers, office space, utilities, etc.—comes to another $300 to $400 per person per month. Then the cost of OCR comes to about $1.2 to $1.6 per page. Taking into account the training period, total volume, time-span, and layoff costs should the operation close down for lack of work, these figures rise to $1.5 to $2.5 per page.
The cost of in-house OCR should be weighed against the cost of outsourcing the work to a professional OCR company. These typically charge from $1.5 to $4 per page, including images and tables. Human Info NGO/Simple Words has such a unit in Romania, and charges humanitarian non-profit organizations a special price that ranges from $1.2 to $2 per page. Please contact us at email@example.com for further information and advice.
3.3 Alternatives to OCR
There are two alternatives to OCR that we discuss here.
One, which eliminates most scanning as well, is to retype the documents manually, using a word processor. This still requires the images and front cover to be scanned, but the remaining pages need not be scanned—thus one can dispense with both powerful scanners and OCR software.
The people who do this work do not have to understand the text. They must be accurate typists and re-key exactly what they see. Retyping does introduce errors, and double-keying is often used to find and correct these. This method involves two people who independently re-key the same document, after which both digital versions are compared word for word using a special software program by an operator who has the original document in front of them. The assumption is that if the same word has been typed independently twice in the same way, it is correct. However, this is not always true, and for extremely high precision, triple-keying is performed.
The advantage of rekeying is that cost is saved because an OCR program is not needed and so the computers can be older, lower-range, or second-hand models—whereas powerful computers are needed for OCR. Also, the work can be performed by people with a lower level of skill. The disadvantages are that a training period of at least two months is needed. Single keying usually produces too many errors, and double or triple keying is needed.
The cost depends entirely on salary level. Typically, re-keyers in developing countries are paid on the order of $150/month. Their productivity could be twenty to thirty pages per day—corresponding to 400 pages per month, images included. With double-keying, this makes the total salary costs around $300 per month, plus overheads.
A very low cost alternative to OCR is simply to use a PDF image version of the document pages. The cost is only a fraction of OCR's—about $0.1 per page.
Once scanning has been completed and TIFF files are available, an automatic converter (usually Adobe Acrobat or Adobe Photoshop) converts all TIFF files of book pages into PDF files.
The downside is that these files are not searchable. Also, they are quite large—usually 50 Kb per page, plus or minus 20% depending on the quality of the original TIFF file.
PDF image files are slow—sometimes, in developing countries, impossible or prohibitively expensive—to download. They rarely fit on a floppy disk, and do not support text manipulation functions such as cut-and-paste.
The PDF image file method should only be used if no OCR budget is available, and for documents that are likely to be used by a small number of people who have high-speed low-cost Internet access.
3.4 Combining scanning and OCR
If a scanner is connected directly to the computer that runs the OCR software, most OCR programs can scan a page and perform OCR immediately. Page-by-page scanning and OCR is a reasonable strategy for low volumes, but will prove time-consuming for bigger and more continuous jobs.
For up to 100 to 150 pages per month, this solution may suffice. For higher volumes it is faster and more efficient to scan the document first, then perfom OCR on all the pages as a separate step.
 Recall that all sums of money are expressed in 2001 US dollars.
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