  Lawn area measurement is an application of image processing and deep
learning. Researchers have been used hierarchical networks, segmented images
and many other methods to measure lawn area. Methods effectiveness and accuracy
varies. In this project Image processing and deep learning methods has been
compared to find the best way to measure the lawn area. Three Image processing
methods using OpenCV has been compared to Convolutional Neural network which is
one of the most famous and effective deep learning methods. We used Keras and
TensorFlow to estimate the lawn area. Convolutional Neural Network or shortly
CNN shows very high accuracy (94-97%) for this purpose. In image processing
methods, Thresholding with 80-87% accuracy and Edge detection are effective
methods to measure the lawn area but Contouring with 26-31% accuracy does not
calculate the lawn area successfully. We may conclude that deep learning
methods especially CNN could be the best detective method comparing to image
processing and other deep learning techniques.
