Classification of Microorganisms of Sukhna and Dhanas Lakes

Published: 11 June 2020| Version 2 | DOI: 10.17632/bcnv3n43wg.2


The dataset consists of morphological features that map the body structure for ten different classes of microorganisms. These microorganisms are found in the lakes of Sukhna and Dhanas, Chandigarh, India. The images of microorganisms were captured by taking microscopic images of whole mounted glass slides. This dataset is used to design and construct a generic intelligent machine learning model and a pipeline of algorithms for classifying multiple microorganisms with a high level of accuracy. Following are the features extracted along with their descriptions. 1. Solidity: It is the ratio of area of an object to the area of a convex hull of the object. Computed as Area/ConvexArea. 2. Eccentricity: The eccentricity is the ratio of length of major to minor axis of an object. 3. EquivDiameter: Diameter of a circle with the same area as the region. 4. Extrema: Extrema points in the region. The format of the vector is [top-left top-right right-top right-bottom bottom-right bottom-left left-bottom left-top]. 5. Filled Area: Number of on pixels in FilledImage, returned as a scalar. 6. Extent: Ratio of the pixel area of a region with respect to the bounding box area of an object. 7. Orientation: The overall direction of the shape. The value ranges from -90 degrees to 90 degrees. 8. Euler number: Number of objects in the region minus the number of holes in those objects. 9. Bounding box: Position and size of the smallest box (rectangle) which bounds the object. 10. Convex hull: Smallest convex shape/polygon that contains the object. 11. Major axis: The major axis is the endpoints of the longest line that can be drawn through the object. Length (in pixels) of the major axis is the largest dimension of the object. 12. Minor axis: The axis perpendicular to the major axis is called the minor axis. Length (in pixels) of the minor axis is the smallest line connecting a pair of points on the contour. 13. Perimeter: Number of pixels around the border of the region. 14. Centroid: Centre of mass of the region. It is a measure of object’s location in the image. 15. Area: Total number of pixels in a region/shape.



University Institute of Engineering and Technology


Image Segmentation, Biodiversity, Image Classification, Lake Management