Mastering OpenCV with Python: Use NumPy, Scikit, TensorFlow, and Matplotlib to learn Advanced algorithms for Machine Learning through a set of Practical Projects by Ayush Vaishya

Mastering OpenCV with Python: Use NumPy, Scikit, TensorFlow, and Matplotlib to learn Advanced algorithms for Machine Learning through a set of Practical Projects by Ayush Vaishya

Author:Ayush Vaishya [Vaishya, Ayush]
Language: eng
Format: epub
ISBN: 9789390475797
Publisher: Orange Education Pvt Ltd, AVA™
Published: 2023-11-15T00:00:00+00:00


Solidity

Solidity is a measure of how closely a shape matches its convex hull, which is the smallest possible convex shape that completely encloses the object. In layman terms, Solidity refers to how solid or filled a shape appears.

If the solidity value is closer to 1, it means that the shape is mostly filled and doesn’t have many holes or concave parts. On the other hand, if the solidity value is closer to 0, it means that the shape has many holes or concave regions, making it less solid.

Solidity is calculated by dividing the contour area by the area of its convex hull representing the proportion of the area covered by the convex hull:

Solidity = (Contour Area) / (Convex Hull Area)

Solidity can be useful in various applications. For example, in object recognition, it can help distinguish between solid objects and objects with holes or concavities or can also be used to filter out irregular shapes or noise in image segmentation tasks.



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