Browse Prior Art Database

MACHINE VISION INSPECTION ALGORITHM OF SEVEN SEGMENT LCDs

IP.com Disclosure Number: IPCOM000005851D
Original Publication Date: 1990-Mar-01
Included in the Prior Art Database: 2001-Nov-12
Document File: 2 page(s) / 114K

Publishing Venue

Motorola

Related People

Pete Kahn: AUTHOR

Abstract

In order to successfully screen common defects present in pager numeric LCD displays a machine vision system may be employed. The machine vision system for this application is a Macintosh II computer with a Data Translation frame grabber board and a Pulnix TM640 CCD camera. This system delivers 256 gray levels and 640 by 460 pixel resolu- tion. The programming was done in RAIL, a language developed by Automatix Inc. RAIL is a high level interpretive language similar to PASCAL with added vision processing functions.

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m MOloRoLA Technical Developments Volume 10 March 1990

MACHINE VISION INSPECTION ALGORITHM OF SEVEN SEGMENT LCDs

by Pete Kahn

   In order to successfully screen common defects present in pager numeric LCD displays a machine vision system may be employed. The machine vision system for this application is a Macintosh II computer with a Data Translation frame grabber board and a Pulnix TM640 CCD camera. This system delivers 256 gray levels and 640 by 460 pixel resolu- tion. The programming was done in RAIL, a language developed by Automatix Inc. RAIL is a high level interpretive language similar to PASCAL with added vision processing functions.

   In order to test all 84 segments of the numeric display shown in FIG-1 a set of 64 regions of interest (windows) whose boundaries overlap each of the segments are used, see FIG-2. An alignment routine to find the best locations of these windows is performed on each LCD prior to running the test algorithm to compensate for fixture and radio tolerances.

Figure 1 - Typical Numeric Pager LCD

Segment Boundary

Figure 2 - Window Boundary Definition

   Next a series of nine pictures are captured while the pager walks through the display sequence shown in FIG-3. For each of the nine captured pictures 64 average gray scale values are calculated and stored, one for each segment. An average gray value of a segment is the average of the pixel values within that segment's window boundary. Therefore, for each of the 64 segments there are nine average gray scale values, two while the segment is on (on avg gray) and 7 while the segment is off (off avg gray). The data collected can be more easily visualized in matrix form as shown in FIG-4.

6.

7.

8.

Figure 3 - Walking Segments Display Sequence

0 Motorola, Inc. 1990 43

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MOTOROLA Technical Developments Volume 10 March 1990

                      SEGMENT # 12 34 5 6 7 8 9 10 11 12 13 14 . . . . . . . . .
1 50203195214208200211 47 204 201 220 206 209 200 . . . . . . . .
2 21045 198210204199210 203 44 198 218208206202 . . . . . .
SNAP SHOT # : :

.

7 208204 194209204 19948 203206199 217208207 49 . . . . .
8 208 204 194 211 205 198 209 203 203 199 217 208 208 198 . . . . . . . . .
9 51 46 52 47 48 44 49 46 46 52 47 48 44 49 . . . . . . . . .

84

197

199

46

45

Figure 4 - 4 Gray Scale Average Result Matrix

Several useful calculations can be made with this measurement matrix to determine whether common functional defects exist in the LCD and are outlined below:

1.

DELTA GRAY - Th...