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35th Applied Imagery and Pattern Recognition Workshop (AIPR'06)
Adaptive Thresholding Based Cell Segmentation for Cell-Destruction Activity Verification
Washington, DC, USA
October 11-October 13
ISBN: 0-7695-2739-6
Praveen Sankaran, Old Dominion University, Norfolk, Virginia
Vijayan K Asari, Old Dominion University, Norfolk, Virginia

An adaptive thresholding method used to distinguish cell boundaries in a given image is presented in this paper. A preprocessing step involves low pass filtering of the image to remove high frequency noise seen in the image. This image is now adaptively thresholded to create a binary image. The bright regions are further analyzed based on their geometrical descriptors such as area and form factor to classify them as cell or non-cell regions.

Two sets of images, pulsed and non-pulsed, are available, which can be compared to determine the efficiency of the pulsing. Results for automatic segmentation are compared with those of manually obtained values to determine its efficiency.

Citation:
Praveen Sankaran, Vijayan K Asari, "Adaptive Thresholding Based Cell Segmentation for Cell-Destruction Activity Verification," aipr, pp.14, 35th Applied Imagery and Pattern Recognition Workshop (AIPR'06), 2006
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