A Review on Otsu Image Segmentation Algorithm

By Hetal J. Vala, Astha Baxi. 2013

421 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/30444378c1189cc9c1597da1abc9e1b868c554c1

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Ishita Das
2. Ujjwal Maulik
3. Nibaran Das
4. M. Abdul
5. M. Mohamad
6. N. Kamarudin
7. S. A. Fadzli
8. Swarnendu Ghosh

Citations in the corpus

• COMPARISON OF IMAGE CLASSIFICATION TECHNIQUES USING CALTECH 101 DATASET (2015, background): “[9] P.”
• Understanding Deep Learning Techniques for Image Segmentation (2019, methodology): “traight forward image segmentation can be assigning class labels to each image based on a threshold-point with respect to the intensity values. One of the earliest algorithm popularly known as Otsu’s [199] method chooses a threshold point with respect to maximum variance. Many modern approaches have”