Phenocam color image calibration using image analysis

2017 ◽  
Author(s):  
Sunoj Shajahan ◽  
Igathinathane Cannayen ◽  
John Hendrickson
Keyword(s):  
Image Analysis ◽  
Color Image ◽  
Image Calibration

Color image analysis for vehicle speed measurement

1993 ◽  
Vol 20 (2) ◽  
pp. 228-235 ◽  
Author(s):  
Yean-Jye Lu ◽  
Xidong Yuan
Keyword(s):  
Image Analysis ◽  
Traffic Control ◽  
Road Traffic ◽  
Color Image ◽  
Image Data ◽  
Difficult Problem ◽  
Vehicle Speed ◽  
Color Image Analysis ◽  
Speed Measurement ◽  
Monochrome Image

Image analysis for traffic data collection has been studied throughout the world for more than a decade. A survey of existing systems shows that research was focused mainly on the monochrome image analysis and that the field of color image analysis was rarely studied. With the application of color image analysis in mind, this paper proposes a new algorithm for vehicle speed measurement in daytime. The new algorithm consists of four steps: (i) image input, (ii) pixel analysis, (iii) single image analysis, and (iv) image sequence analysis. It has three significant advantages. First, the algorithm can distinguish the shadows caused by moving vehicles outside the detection area from the actual vehicles passing through the area, which is a difficult problem for the monochrome image analysis technique to handle. Second, the algorithm significantly reduces the image data to be processed; thus only a personal computer is required without the addition of any special hardware. The third advantage is the flexible placement of detection spots at any position in the camera's field of view. The accuracy of the algorithm is also discussed. Key words: speed measurement, vehicle detection, image analysis, image processing, traffic control, traffic measurement and road traffic.

QUANTIFICATION OF STEROID RECEPTORS IN BREAST CANCER BY COLOR IMAGE ANALYSIS

1991 ◽  
Vol 73 (2-3) ◽  
pp. 37a-37a
Author(s):  
Philippe Rostagno ◽  
Francette Ettore ◽  
Cyril Caldani
Keyword(s):  
Breast Cancer ◽  
Image Analysis ◽  
Color Image ◽  
Steroid Receptors ◽  
Color Image Analysis

Calibration of Conodont Color Alteration Using Color Image Analysis

1995 ◽  
Vol 103 (3) ◽  
pp. 257-267 ◽  
Author(s):  
S. Helsen ◽  
P. David ◽  
W. J. J. Fermont
Keyword(s):  
Image Analysis ◽  
Color Image ◽  
Color Image Analysis ◽  
Color Alteration

SOIL COVER DETERMINATION USING COLOR IMAGE ANALYSIS ON SKIDDING COST

1990 ◽  
Vol 33 (4) ◽  
pp. 1402-1409 ◽  
Author(s):  
Y. J. Han ◽  
J. C. Hayes
Keyword(s):  
Image Analysis ◽  
Soil Cover ◽  
Color Image ◽  
Color Image Analysis

scholarly journals Flow Visualization in Intersecting Ducts by Color Image Analysis

1996 ◽  
Vol 16 (1Supplement) ◽  
pp. 273-276
Author(s):  
Shinzaburo UMEDA ◽  
Wen-Jei YANG ◽  
Yoshiaki UETANI
Keyword(s):  
Image Analysis ◽  
Flow Visualization ◽  
Color Image ◽  
Color Image Analysis

scholarly journals IDENTIFICATION OF MEGALOBLASTIC ANEMIA CELLS THROUGH THE USE OF IMAGE PROCESSING TECHNIQUES

2018 ◽  
Vol 4 (3) ◽  
pp. 1-5 ◽  
Author(s):  
Asaad Babker ◽  
Vyacheslav Lyashenko
Keyword(s):  
Image Processing ◽  
Image Analysis ◽  
Blood Smear ◽  
Color Image ◽  
Megaloblastic Anemia ◽  
Cell Structure ◽  
Color Space ◽  
Image Processing Techniques ◽  
Processing Techniques ◽  
Blood Smear Image

Objective: Our aim is to show the possibility of using different image processing techniques for blood smear analysis. Also our aim is to determine the sequence of image processing techniques to identify megaloblastic anemia cells. Methods: We consider blood smear image. We use a variety of image processing techniques to identify megaloblastic anemia cells. Among these methods, we distinguish the modification of the color space and the use of wavelets. Results: We developed a sequence of image processing techniques for blood smear image analysis and megaloblastic anemia cells identification. As a characteristic feature for megaloblastic anemia cells identification, we consider neutrophil image structure. We also use the morphological methods of image analysis in order to reveal the nuclear lobes in neutrophil structure. Conclusion: We can identify the megaloblastic anemia cells. To do this, we use the following sequence of blood smear image processing: color image modification, change of the image contrast, use of wavelets and morphological analysis of the cell structure. 

Protein Determination by Ponceau S Using Digital Color Image Analysis of Protein Spots on Nitrocellulose Membranes

1999 ◽  
Vol 267 (2) ◽  
pp. 382-389 ◽  
Author(s):  
Sanjay V. Bannur ◽  
Sunil V. Kulgod ◽  
Shalaka S. Metkar ◽  
Suresh K. Mahajan ◽  
Jayashree K. Sainis
Keyword(s):  
Image Analysis ◽  
Color Image ◽  
Protein Determination ◽  
Color Image Analysis ◽  
Ponceau S
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