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Computer Vision of Microwave Treated red Kidney Beans (Rajma)


Affiliations
1 CSIR-National Physical Laboratory, New Delhi 110 012, India

IMAQ vision development module and LabVIEW based programming is potentially useful for analysis of untreated and treated red kidney beans. The IMAQ vision development tool and LabVIEW based programming used several algorithms to display the boundary values, edge detection, length and width of the red kidney beans present in the captured images by webcam. In addition, application of image processing has been used for the threshold conditions and number of edges present in the images. These edges and threshold conditions describe the information about the red kidney beans. A test result has shown the ROI histogram to detect the pixels intensity along with standard deviation and mean value of the images. Resultant coefficient of determination has shown the percentage variation in red, green and blue plane such as 35.78%, 37.33% and 46.38% respectively. It is necessary to count the insects’ eggs on surface of red kidney beans to avoid the hatching of insects’ eggs before and after treatment. In this paper we have used method for counting the insects’ egg count on surface of red kidney beans in the captured images.

Keywords

LabVIEW, IMAQ vision, Image processing, Grain size, Histogram, Color, Insect’s egg identification, Red kidney beans
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  • Computer Vision of Microwave Treated red Kidney Beans (Rajma)

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Authors

Chitra Gautam
CSIR-National Physical Laboratory, New Delhi 110 012, India

Abstract


IMAQ vision development module and LabVIEW based programming is potentially useful for analysis of untreated and treated red kidney beans. The IMAQ vision development tool and LabVIEW based programming used several algorithms to display the boundary values, edge detection, length and width of the red kidney beans present in the captured images by webcam. In addition, application of image processing has been used for the threshold conditions and number of edges present in the images. These edges and threshold conditions describe the information about the red kidney beans. A test result has shown the ROI histogram to detect the pixels intensity along with standard deviation and mean value of the images. Resultant coefficient of determination has shown the percentage variation in red, green and blue plane such as 35.78%, 37.33% and 46.38% respectively. It is necessary to count the insects’ eggs on surface of red kidney beans to avoid the hatching of insects’ eggs before and after treatment. In this paper we have used method for counting the insects’ egg count on surface of red kidney beans in the captured images.

Keywords


LabVIEW, IMAQ vision, Image processing, Grain size, Histogram, Color, Insect’s egg identification, Red kidney beans