MARC details
| 000 -LEADER |
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| fixed length control field |
02353nam a2200265 a 4500 |
| 001 - CONTROL NUMBER |
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| control field |
vtls000067664 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
KUKTEM |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20251114204533.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
121212t2012 my a f m 000 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
THE0002938(Local) |
| 039 #9 - LEVEL OF BIBLIOGRAPHIC CONTROL AND CODING DETAIL [OBSOLETE] |
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| Level of rules in bibliographic description |
201905140824 |
| Level of effort used to assign nonsubject heading access points |
zul |
| -- |
201212120955 |
| -- |
ida |
| 040 ## - CATALOGING SOURCE |
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| Original cataloging agency |
UMP |
| 090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN) |
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| Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) |
TA1634 .L54 2012 rs Bc. |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Liew, Kok Wah |
| 245 13 - TITLE STATEMENT |
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| Title |
An efficient approach for vision inspection of IC chips / |
| Statement of responsibility, etc. |
Liew Kok Wah |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
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| Place of publication, distribution, etc. |
Kuantan, Pahang : |
| Name of publisher, distributor, etc. |
UMP, |
| Date of publication, distribution, etc. |
2012 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xii, 41 p. : |
| Other physical details |
ill. ; |
| Dimensions |
30 cm. + |
| Accompanying material |
1 CD-ROM |
| 502 ## - DISSERTATION NOTE |
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| Dissertation note |
Project paper (Bachelor of Computer Science (Graphics and Multimedia Technology)) - Universiti Malaysia Pahang - 2012 |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
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| Bibliography, etc. note |
Bibliography : p. 38-39 |
| 520 3# - SUMMARY, ETC. |
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| Summary, etc. |
The research aims to develop an automated vision inspection system of IC chips that used to detect the defects of marking and design shape of IC chips. As a result of higher failure probability of manual inspection system, this automated system is developed. The automated vision system will consists of five main phases which are image acquisition, image enhancement, image, segmentation, comparison on features and decision making. The features will be extracted from the target image using projection profile method. The decision will be made using the trained neural network to identify the four common defects of IC chips which are illegible marking, upside down marking and missing character on chip. The results of the automated system are to determine whether to accept or reject the chip. The results are computed within 10 seconds and have a high percentage of defects detection which is about 95 %. Through the results obtained, the automated vision inspection system of IC chips can be utilized in the manufacturing field to replace the manual inspection system. It can replace about five to eight inspection experts to reduce the cost of hiring and resources in about 70%. Other than that, the rate of accuracy and efficiency of detecting the defects are improved by 95% because the consistency of inspecting the chips is maintained from having variations of judgments by the experts. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
Machine vision |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
Image processing |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
Integrated circuit industry |