Image Acquisitionand Proces

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Machine Vision 219 TABLE 8.1 “IMAQ OCR Recognition Config” Parameters Input Maximum point size Language Character set Character type Recognition mode Auto correction Output delimiter Description The OCR routine will only recognize text with a point size of this value or less (this value should be set to a value slightly above your expected point size). The OCR routine can recognize characters in English, French and Spanish. If you know that the text you are trying to return has only uppercase letters, then you can instruct the OCR routine not to try and Þnd other characters (lowercase letters, numbers, punctuation, etc). Limiting the character set will not only increase the speed of the OCR routine dramatically, but also inhibit common errors (for example, mistaking I for l). This input instructs the OCR routine to whether the expected text is normal, italic or a mixture of both (note: type checking is performed on a word-level, so mixing normal and italic characters within a word may cause the OCR routine to fail). There are four recognition modes: High Speed (Very fast, only good for low noise images with well spaced and deÞned characters). Nominal (Down-samples images to 200 dpi before scanning to improve speed — nominal and balanced are identical when source images that are already 200 dpi or less). Balanced (Good for a wide range of typeface variations and character qualities). Unoptimized (Disables all recognition optimizations). When enabled, auto correction will cause the OCR routine to attempt to Þnd the closest match to characters that it does not recognize at all. If disabled, unrecognized characters are ignored. This setting is only useful if you want to change the character that will appear between detected words. The available settings are None (disables the delimiter), Space (default), Tab, Comma and Full Stop (“Dot”).
220 <strong>Image</strong> Acquisition <strong>Proces</strong>sing with LabVIEW Several letters and numbers in the OCR’s character library look similar: Character Similar Characters The letter I 1 l i ! | / \ [ ] ' The letter S 5 $ The letter O 0 Ø W o Using these example characters, you can see how simple text can be incorrectly parsed: Printed String Possible OCR Results ISO 9001 ISO 9001 1SO 900I !SO 900[ I$Ø 9WW| [50 9OO] \$Ø 9WW/ |S0 900| iSo 9oo! ... Using IMAQ OCR Correction Config, you can set the way ambiguously detected characters are interpreted. The VI has the inputs shown in Table 8.2. TABLE 8.2 “IMAQ OCR Correction Config” Inputs Input Character preference Method Aggressiveness Description This input depends on whether you want the OCR routines to favor alphabetic or numeric characters, or neither. For example, setting the character preference to alphabetic will prevent errors such as ISO Þ 1S0. The method input is similar to the recognition mode input for IMAQ OCR Recognition ConÞg. Using this input, you are able to place more emphasis on whether the correction is faster or more accurate (default). Aggressiveness deÞnes to what extent the OCR search will attempt to parse a character that is ambiguous. When the OCR search detects a character that it is not sure about, it will compare it to a list of characters to Þnd a possible match, and setting the aggressiveness changes the list of characters to be searched: Conservative List: Aggressive List: 1I l | ! ] [ 0 O 1 I l | ! ] [ 0 O 2 Z 5 S 8 B As you might expect, using the aggressive list will slow down OCR searching of ambiguous text. 8.1.3 OCR PROCESSING Once you have set both the OCR recognition and correction parameters, all that remains to do is to perform the OCR search. There are two OCR searchVIs available in the Vision Toolkit: IMAQ Basic OCR and IMAQ Complex OCR. The only difference
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IMAGE PROCESSING SERIES Series Edit
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Foreword The introduction of LabVIE
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FIGURE 1 Vision 6.1 FIGURE 2 Compan
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Acknowledgments My gratitude goes o
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Dedication To Don “old fella” P
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Contents Chapter 1 Image Types and
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Chapter 4 Displaying Images........
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Chapter 7 Image Analysis...........
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1 Image Types and File Management F
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Image Types and File Management 3 F
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Image Types and File Management 5 A
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Image Types and File Management 7 C
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Image Types and File Management 9 p
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Image Types and File Management 11
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Image Types and File Management 13
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2 Setting Up You should never under
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Setting Up 17 FIGURE 2.3 (a) Interl
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Setting Up 19 Linear Aray Light Sou
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Setting Up 21 FIGURE 2.7 National I
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Setting Up 23 2.1.3.2 Control and I
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Setting Up 25 FIGURE 2.11 X-Ray ima
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Setting Up 27 Apple Computer techno
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Setting Up 29 FIGURE 2.17 An inexpe
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Setting Up 31 Although this would b
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Setting Up 33 134 -115 \ Contrast =
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Setting Up 35 resolution printer wi
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Setting Up 37 C A B C Traditional T
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Setting Up 39 Camera Light Source O
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Setting Up 41 Camera Light Source (
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Setting Up 43 FIGURE 2.37 (a) An ob
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Setting Up 45 FIGURE 2.41 (a) PCB p
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48 Image Acquisition Processing wit
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6 Morphology When applied to vision
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Morphology 143 I Closed { } = Erode
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Morphology 145 FIGURE 6.3 Simple mo
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Morphology 147 FIGURE 6.5 Custom st
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Morphology 149 FIGURE 6.8 Particle
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Morphology 151 FIGURE 6.12 Fill hol
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Morphology 153 FIGURE 6.17 Danielss
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Morphology 155 Detected circles wit
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Morphology 157 6.5 CASE STUDY: FIND
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Morphology 159 6.6 USER SOLUTION: D
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Morphology 161 ULTRASOUND MACHINE (
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Morphology 163 FIGURE 6.31 The Edit
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Image Acquisitionand Proces

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