Journals Information
Computer Science and Information Technology Vol. 2(7), pp. 287 - 295
DOI: 10.13189/csit.2014.020701
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Luminance-Free Color Detection for Quantification and Automatic Segmentation in Microscopy: A Methodological Approach
Teresa Lettini 1,*, Gabriella Serio 1, Tiziana Valente 2, Flavio Ceglie 2, Alessandra Punzi 1, Rosalia Ricco 1, Vittorio Pesce Delfino 2
1 Dept. Emergency and Organ Transplantation (DETO), Sect. of Pathology, Medical School, University of Bari 11 G. Cesare Square, 70124, Bari, Italy
2 Digamma Research Centre, Bari
ABSTRACT
This procedure is aimed at solving the chromatic quantification problem in histological images, as well as other fields. On digital images, this is possible using colorimetric software applications. Our solution was to adopt a pre-processing step of the analog signal coming from a video-source (cabling a suitable, dedicated unit to the video-line before signal grabbing). The unit is a hardware device that processes the voltage values of the video signal image section, line by line in the raster image exploiting the vertical interval. The output is a luminance-free video signal compatible with real-time needs (1/25 second), that is in turn compatible with the normal exploration speed of a histological slide. Some experimental results are presented.
KEYWORDS
Chromatic Quantification, Microscopic Images, Immunohistochemistry
Cite This Paper in IEEE or APA Citation Styles
(a). IEEE Format:
[1] Teresa Lettini , Gabriella Serio , Tiziana Valente , Flavio Ceglie , Alessandra Punzi , Rosalia Ricco , Vittorio Pesce Delfino , "Luminance-Free Color Detection for Quantification and Automatic Segmentation in Microscopy: A Methodological Approach," Computer Science and Information Technology, Vol. 2, No. 7, pp. 287 - 295, 2014. DOI: 10.13189/csit.2014.020701.
(b). APA Format:
Teresa Lettini , Gabriella Serio , Tiziana Valente , Flavio Ceglie , Alessandra Punzi , Rosalia Ricco , Vittorio Pesce Delfino (2014). Luminance-Free Color Detection for Quantification and Automatic Segmentation in Microscopy: A Methodological Approach. Computer Science and Information Technology, 2(7), 287 - 295. DOI: 10.13189/csit.2014.020701.