語系:
繁體中文
English
說明(常見問題)
回圖書館首頁
手機版館藏查詢
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Quality inspection for cheese packag...
~
Cheng, Zhe.
FindBook
Google Book
Amazon
博客來
Quality inspection for cheese packaging using machine vision and image processing.
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Quality inspection for cheese packaging using machine vision and image processing./
作者:
Cheng, Zhe.
面頁冊數:
102 p.
附註:
Source: Masters Abstracts International, Volume: 52-03.
Contained By:
Masters Abstracts International52-03(E).
標題:
Engineering, Computer. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1548021
ISBN:
9781303523045
Quality inspection for cheese packaging using machine vision and image processing.
Cheng, Zhe.
Quality inspection for cheese packaging using machine vision and image processing.
- 102 p.
Source: Masters Abstracts International, Volume: 52-03.
Thesis (M.S.E.)--Purdue University, 2013.
The acumen and sophistication of consumers have created the increasing expectation for improved quality in food product, which is considered as the essential element of daily life. In turn, this has encouraged food producers to improve their quality monitoring by deploying enhanced computer quality inspection technologies [1]. The aim of this thesis is to design an efficient and adaptable algorithm to accurately and efficiently monitor the quality of the packaged cheeses on the assembly line. Computer vision and image processing methods were used to distinguish unqualified cheeses from a large amount of samples. The criteria for classification were consisted of two main aspects, similarity of cheese shape and leakage condition. Gray and binary cheese images were converted from the original pictures, which were captured by cameras. The cheese part was extracted from the background for shape analysis to generate its signature, which was then compared with the signature of the standard cheese shape to measure the similarity by the cross-correlation method. Cheese leakage in the remaining part was discovered by setting a certain range of RGB value, which was subject to the condition of light sources. Two thresholds were set to control the detection result, which was intended x to best match human perception. Sensitivity, specificity, accuracy and receiver operating characteristic (ROC) were used to evaluate the algorithm's performance.
ISBN: 9781303523045Subjects--Topical Terms:
1669061
Engineering, Computer.
Quality inspection for cheese packaging using machine vision and image processing.
LDR
:02335nam a2200289 4500
001
1964203
005
20141015113810.5
008
150210s2013 ||||||||||||||||| ||eng d
020
$a
9781303523045
035
$a
(MiAaPQ)AAI1548021
035
$a
AAI1548021
040
$a
MiAaPQ
$c
MiAaPQ
100
1
$a
Cheng, Zhe.
$3
1270890
245
1 0
$a
Quality inspection for cheese packaging using machine vision and image processing.
300
$a
102 p.
500
$a
Source: Masters Abstracts International, Volume: 52-03.
500
$a
Adviser: Bin Chen.
502
$a
Thesis (M.S.E.)--Purdue University, 2013.
520
$a
The acumen and sophistication of consumers have created the increasing expectation for improved quality in food product, which is considered as the essential element of daily life. In turn, this has encouraged food producers to improve their quality monitoring by deploying enhanced computer quality inspection technologies [1]. The aim of this thesis is to design an efficient and adaptable algorithm to accurately and efficiently monitor the quality of the packaged cheeses on the assembly line. Computer vision and image processing methods were used to distinguish unqualified cheeses from a large amount of samples. The criteria for classification were consisted of two main aspects, similarity of cheese shape and leakage condition. Gray and binary cheese images were converted from the original pictures, which were captured by cameras. The cheese part was extracted from the background for shape analysis to generate its signature, which was then compared with the signature of the standard cheese shape to measure the similarity by the cross-correlation method. Cheese leakage in the remaining part was discovered by setting a certain range of RGB value, which was subject to the condition of light sources. Two thresholds were set to control the detection result, which was intended x to best match human perception. Sensitivity, specificity, accuracy and receiver operating characteristic (ROC) were used to evaluate the algorithm's performance.
590
$a
School code: 0183.
650
4
$a
Engineering, Computer.
$3
1669061
650
4
$a
Agriculture, Food Science and Technology.
$3
1017813
650
4
$a
Engineering, Packaging.
$3
1025152
690
$a
0464
690
$a
0359
690
$a
0549
710
2
$a
Purdue University.
$b
Computer Engineering.
$3
2100611
773
0
$t
Masters Abstracts International
$g
52-03(E).
790
$a
0183
791
$a
M.S.E.
792
$a
2013
793
$a
English
856
4 0
$u
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1548021
筆 0 讀者評論
館藏地:
全部
電子資源
出版年:
卷號:
館藏
1 筆 • 頁數 1 •
1
條碼號
典藏地名稱
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
W9259202
電子資源
11.線上閱覽_V
電子書
EB
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
評論
新增評論
分享你的心得
Export
取書館
處理中
...
變更密碼
登入