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Application of machine vision to hum...

Guyer, Daniel Earl.

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Application of machine vision to human shape analysis techniques in leaf and plant identification: An intelligent vision structure.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Application of machine vision to human shape analysis techniques in leaf and plant identification: An intelligent vision structure./
Author:	Guyer, Daniel Earl.
Description:	223 p.
Notes:	Source: Dissertation Abstracts International, Volume: 50-03, Section: B, page: 1032.
Contained By:	Dissertation Abstracts International50-03B.
Subject:	Engineering, Agricultural. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=8911911

Application of machine vision to human shape analysis techniques in leaf and plant identification: An intelligent vision structure.
Guyer, Daniel Earl.

Application of machine vision to human shape analysis techniques in leaf and plant identification: An intelligent vision structure. - 223 p.

Source: Dissertation Abstracts International, Volume: 50-03, Section: B, page: 1032.

Thesis (Ph.D.)--Purdue University, 1988.

Intelligent vision systems capable of automatically interpreting images are the next generation in machine vision. These systems will be functional to nonexperts in the machine vision field, and will be flexible and reprogrammable for general use. Addition of intelligence into vision systems requires an understanding and structuring of human visual and scene interpretation techniques.Subjects--Topical Terms:

1019504
Engineering, Agricultural.

Application of machine vision to human shape analysis techniques in leaf and plant identification: An intelligent vision structure.
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008 150210s1988 ||||||||||||||||| ||eng d
035 $a (MiAaPQ)AAI8911911
035 $a AAI8911911
040 $a MiAaPQ $c MiAaPQ
100 1 $a Guyer, Daniel Earl. $3 2105768
245 1 0 $a Application of machine vision to human shape analysis techniques in leaf and plant identification: An intelligent vision structure.
300 $a 223 p.
500 $a Source: Dissertation Abstracts International, Volume: 50-03, Section: B, page: 1032.
500 $a Major Professor: Gaines E. Miles.
502 $a Thesis (Ph.D.)--Purdue University, 1988.
520 $a Intelligent vision systems capable of automatically interpreting images are the next generation in machine vision. These systems will be functional to nonexperts in the machine vision field, and will be flexible and reprogrammable for general use. Addition of intelligence into vision systems requires an understanding and structuring of human visual and scene interpretation techniques.
520 $a This research was designed to investigate the interrelationships and combine the areas of image processing, feature extraction and techniques of human scene interpretation. The research is especially unique in its rule-based structuring of subjective, qualitative human-level shape features and quantitative machine-level shape features. Additionally a unique approach was implemented to extract plant/leaf shape features using information gathered from critical points along object borders. The critical points were determined using the object's centroid. The image processing portion of the program followed a procedural format with examples of images processed by various routines displayed on a screen for user evaluation, which allowed the system to act as a programming aid.
590 $a School code: 0183.
650 4 $a Engineering, Agricultural. $3 1019504
650 4 $a Artificial Intelligence. $3 769149
690 $a 0539
690 $a 0800
710 2 $a Purdue University. $3 1017663
773 0 $t Dissertation Abstracts International $g 50-03B.
790 $a 0183
791 $a Ph.D.
792 $a 1988
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=8911911