scholarly journals CLASSIFICATION OF APPLE DEFECTED FRUITS USING COLOR IMAGE ANALYSIS TECHNIQUE

2013 ◽  
Vol 30 (2) ◽  
pp. 487-506
Author(s):  
A. A. Abd El-Rahman
2011 ◽  
Vol 26 (3) ◽  
pp. 111 ◽  
Author(s):  
Olivier Lezoray ◽  
Michel Lecluse

Broncho alveolar lavage is the most commonly used diagnostic tool for confirming alveolar hemorrhage. Golde has introduced a ranking score, based on the hemosiderin content of macrophages which enables ranking cells from 0 to 4 based on the degree of Prussian blue stain. We propose a complete image analysis scheme to automatically perform both the extraction of the cellular objects and the ranking of each cell according to the Golde score. The image analysis techniques used mainly involve clustering and mathematical morphology. A 2D histogram is clustered to extract the main cellular components, a color watershed is used to determine and refine the regions. Finally, the cellular components of interest are firstly classified according to their hue and secondly according to their staining repartition. The proposed image analysis technique is very fast and produces reliable and accurate results.


1993 ◽  
Vol 20 (2) ◽  
pp. 228-235 ◽  
Author(s):  
Yean-Jye Lu ◽  
Xidong Yuan

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.


1991 ◽  
Vol 73 (2-3) ◽  
pp. 37a-37a
Author(s):  
Philippe Rostagno ◽  
Francette Ettore ◽  
Cyril Caldani

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

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