Quantitative detection of the colloidal gold immunochromatographic strip in HSV color space

Yuanshu Wu; Yueming Gao; Min Du

doi:10.1117/12.2068033

18 September 2014 Quantitative detection of the colloidal gold immunochromatographic strip in HSV color space

Yuanshu Wu, Yueming Gao, Min Du

Proceedings Volume 9282, 7th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optical Test and Measurement Technology and Equipment; 928231 (2014) https://doi.org/10.1117/12.2068033
Event: 7th International Symposium on Advanced Optical Manufacturing and Testing Technologies (AOMATT 2014), 2014, Harbin, China

Abstract

In this paper, a fast, reliable and accurate quantitative detection method for the colloidal gold immunochromatographic strip(GICA) is presented. An image acquisition device which is mainly composed of annular LED source, zoom ratio lens, and 10bit CMOS image sensors with 54.5dB SNR is designed for the detection. Firstly, the test line is extracted from the strip window through using the H component peak points of the HSV space as the clustering centers via the Fuzzy C-Means(FCM) clustering method. Then, a two dimensional eigenvalue composed with the hue(H) and saturation(S) of HSV space was proposed to improve the accuracy of the quantitative detection. At last, the experiment of human chorionic gonadotropin(HCG) with the concentration range 0-500mIU/mL is carried out. The results show that the linear correlation coefficient between this method and optical density(OD) values measured by the fiber optical sensor reach 96.74%. Meanwhile, the linearity of fitting curve constructed with concentration was greater than 95.00%.

Citation Download Citation

Yuanshu Wu, Yueming Gao, and Min Du "Quantitative detection of the colloidal gold immunochromatographic strip in HSV color space", Proc. SPIE 9282, 7th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optical Test and Measurement Technology and Equipment, 928231 (18 September 2014); https://doi.org/10.1117/12.2068033

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KEYWORDS

Gold

RGB color model

Image processing

Image acquisition

Image quality

CMOS sensors

Image segmentation

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