@article{(Open Science Index):https://publications.waset.org/pdf/2654,
	  title     = {Hot-Spot Blob Merging for Real-Time Image Segmentation},
	  author    = {K. Kraus and  M. Uiberacker and  O. Martikainen and  R. Reda},
	  country	= {},
	  institution	= {},
	  abstract     = {One of the major, difficult tasks in automated video
surveillance is the segmentation of relevant objects in the scene.
Current implementations often yield inconsistent results on average
from frame to frame when trying to differentiate partly occluding
objects. This paper presents an efficient block-based segmentation
algorithm which is capable of separating partly occluding objects and
detecting shadows. It has been proven to perform in real time with a
maximum duration of 47.48 ms per frame (for 8x8 blocks on a
720x576 image) with a true positive rate of 89.2%. The flexible
structure of the algorithm enables adaptations and improvements with
little effort. Most of the parameters correspond to relative differences
between quantities extracted from the image and should therefore not
depend on scene and lighting conditions. Thus presenting a
performance oriented segmentation algorithm which is applicable in
all critical real time scenarios.},
	    journal   = {International Journal of Electrical and Computer Engineering},
	  volume    = {2},
	  number    = {10},
	  year      = {2008},
	  pages     = {2167 - 2172},
	  ee        = {https://publications.waset.org/pdf/2654},
	  url   	= {https://publications.waset.org/vol/22},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 22, 2008},