Calibration of a video image analysis system for measurement of stem length, leaf area, and percent ground coverage

1998 ◽  
Vol 29 (9-10) ◽  
pp. 1071-1081 ◽  
Author(s):  
Reuben B. Beverly ◽  
Marc W. van Iersel
Keyword(s):  
Image Analysis ◽  
Leaf Area ◽  
Video Image ◽  
Stem Length ◽  
Image Analysis System ◽  
Video Image Analysis ◽  
Ground Coverage ◽  
Analysis System

Direct Observation of Capillary Electrophoretic Phenomena Using Video Image Analysis System

1996 ◽  
Vol 25 (1) ◽  
pp. 93-94 ◽  
Author(s):  
Saeid Razee ◽  
Atsushi Tamura ◽  
Masumeh Khademizadeh ◽  
Tsutomu Masujima
Keyword(s):  
Image Analysis ◽  
Direct Observation ◽  
Video Image ◽  
Image Analysis System ◽  
Video Image Analysis ◽  
Capillary Electrophoretic ◽  
Analysis System

Beef Carcass Evaluation by Use of a Video Image Analysis System

1983 ◽  
Vol 57 (4) ◽  
pp. 908-917 ◽  
Author(s):  
H. R. Cross ◽  
D. A. Gilliland ◽  
P. R. Durland ◽  
S. Seideman
Keyword(s):  
Image Analysis ◽  
Video Image ◽  
Image Analysis System ◽  
Video Image Analysis ◽  
Analysis System ◽  
Beef Carcass

A video image analysis system for concentration measurements and flow visualization in building wakes

1991 ◽  
Vol 25 (7) ◽  
pp. 1211-1225 ◽  
Author(s):  
J.T. Lee ◽  
Darrell L. Call ◽  
Robert E. Lawson ◽  
William E. Clements ◽  
Donald E. Hoard
Keyword(s):  
Image Analysis ◽  
Flow Visualization ◽  
Video Image ◽  
Image Analysis System ◽  
Video Image Analysis ◽  
Concentration Measurements ◽  
Analysis System

scholarly journals Grading Peanut Butter Using Video Image Analysis Techniques1

1987 ◽  
Vol 14 (2) ◽  
pp. 74-79 ◽  
Author(s):  
T. B. Whitaker ◽  
J. W. Dickens ◽  
A. B. Slate
Keyword(s):  
Image Analysis ◽  
Peanut Butter ◽  
Video Image ◽  
Image Analysis System ◽  
Agricultural Marketing ◽  
Video Image Analysis ◽  
Color Indices ◽  
Marketing Service ◽  
Analysis System ◽  
Good Agreement

Abstract A video image analysis system was designed to quantitatively measure the amount of specks and the color of peanut butter samples for grade purposes. The video image of a peanut butter surface 5.8 cm by 5.8 cm was captured and converted into 384 by 384 picture elements (pixels). The intensity of each of the 147,456 pixels was classified into one of 256 shades of gray from zero for black to 255 for white. The percent of total pixels that represented specks was defined as the speck index. The aveage shade of gray of all 147,456 pixels was defined as the color index. The speck and color indices were computed for 52 peanut butter samples that had been graded by experienced Agricultural Marketing Service (AMS) inspectors. The speck and color indices were both in good agreement with the AMS speck and color classifications assigned to the samples by the AMS inspectors.

Evaluation of the E+V video image analysis system as a predictor of pork carcass meat yield1

2003 ◽  
Vol 81 (5) ◽  
pp. 1193-1201 ◽  
Author(s):  
E. K. McClure ◽  
J. A. Scanga ◽  
K. E. Belk ◽  
G. C. Smith
Keyword(s):  
Image Analysis ◽  
Video Image ◽  
Image Analysis System ◽  
Video Image Analysis ◽  
Analysis System
Sign in / Sign up

Export Citation Format

Share Document