Method of detecting defects in semiconductor package leads

• US 5,452,368 A
• Filed: 08/02/1993
• Issued: 09/19/1995
• Est. Priority Date: 08/02/1993
• Status: Expired due to Fees

• Current Assignee: Freescale Semiconductor, Inc. (NXP Semiconductors NV)
• Original Assignee: Motorola, Inc. (Motorola Solutions, Inc.)
• Inventors: LeBeau, Christopher J.
• Primary Examiner(s): Mancuso, Joseph
• Assistant Examiner(s): DEL ROSSO, GERARD DOMNICK
• Application Number:
  US08/100,829
• Time in Patent Office: 778 Days
• Field of Search: 382/8, 382/55, 382/1, 382/34, 348/126, 348/129, 356/237
• US Class Current: 382/145
• CPC Class Codes: G01R 31/308 using non-ionising electromagnetic radiation, e.g. optical radiation investigating or analysing materials by the use of optical means G01N21/00; image analysis G06T7/00
• CPC Class Codes: G06T 2207/30141 Printed circuit board [PCB]
• CPC Class Codes: G06T 2207/30148 Semiconductor; IC; Wafer
• CPC Class Codes: G06T 7/0004 Industrial image inspection

Abstract

A method of detecting defects (14, 16, 17, 44, 47, 49, and 51) in objects is presented. A first grey level image (18) of a first object (10) is formed and a second grey level image (19) of a second object (12) is formed. The first (18) and second (19) grey level images are converted to a first (21) and a second (22) edge feature image, respectively. The first edge feature image is dilated (26) and the second edge feature image is skeletonized (27). The dilated (26) and skeletonized images (27) are compared. An alternate method includes forming a grey level image (40) of an object. A principal axis of the grey level image is identified, and a shifted grey level image is formed by shifting the grey level image a distance along the principal axis. The grey level image (40) is then compared to the shifted grey level image.

Claims

1. A method of detecting defects in leads of a semiconductor package comprising:

providing a first semiconductor package having a first conductive line;

acquiring a first grey level image of the first conductive line;

providing a second semiconductor package having a second conductive line;

acquiring a second grey level image of the second conductive line;

converting the first grey level image to a first edge feature image;

converting the second grey level image to a second edge feature image;

skeletonizing the first edge feature image to form a first skeletonized image;

dilating the second edge feature image to form a first dilated image;

comparing the first skeletonized image to the first dilated image;

detecting shapes in the first skeletonized image that are not contained within the first dilated image;

skeletonizing the second edge feature image to form a second skeletonized image;

dilating the first edge feature image to form a second dilated image;

comparing the second skeletonized image to the second dilated image; and

detecting shapes in the second skeletonized image that are not contained within the second dilated image.

2. The method of claim 1 wherein detecting shapes includes sorting the shapes by size.

3. The method of claim 1 wherein comparing the first skeletonized image to the first dilated image includes subtracting the first skeletonized image from the first dilated image.

4. The method of claim 1 wherein comparing the second skeletonized image to the second dilated image includes subtracting the second skeletonized image from the second dilated image.

5. The method of claim 1 wherein skeletonizing the first edge feature image includes reducing a width of the first edge feature to approximately one pixel.

6. The method of claim 1 wherein dilating the first edge feature image includes increasing a width of the first edge feature by approximately 10 to 50 percent.

7. A method of detecting defects in an object comprising:

converting a first grey level image of a first object to a first edge feature image;

converting a second grey level image of a second object to a second edge feature image;

skeletonizing the first edge feature image to form a first skeletonized image;

dilating the second edge feature image to form a first dilated image;

comparing the first skeletonized image to the first dilated image;

skeletonizing the second edge feature image to form a second skeletonized image;

dilating the first edge feature image to form a second dilated image;

comparing the second skeletonized image to the second dilated image; and

detecting shapes in the first skeletonized image that are not contained within the first dilated image.

8. The method of claim 7 wherein detecting shapes includes sorting the shapes by size.

9. The method of claim 7 wherein comparing the first skeletonized image to the first dilated image includes subtracting the first skeletonized image from the first dilated image.

10. The method of claim 7 wherein skeletonizing the first edge feature image includes reducing a width of the first edge feature to approximately one pixel.

11. The method of claim 7 wherein dilating the second edge feature image includes increasing a width of the first edge feature by approximately 10 to 50 percent.