Removing High Density Impulse Noise Via a Novel Two Phase Method Using Fuzzy Cellular Automata

Mohammad Mehdi Piroozmandan; Fardad Farokhi; Kaveh Kangarloo

Volume 10, Issue 04 , November 2021, , Pages 177-186

  In this paper, a novel method named RHDINTPM (Removing High Density Impulse Noise via a Novel Two Phase Method) is proposed for de-noising digital images corrupted by impulse noise. The proposed method is based on cellular automata (CA) and fuzzy cellular automata (FCA). In this method, a given image ...  Read More

Effective Feature Selection for Pre-Cancerous Cervix Lesions Using Artificial Neural Networks

Farnaz Rouhbakhsh; Fardad Farokhi; Kaveh Kangarloo

Volume 01, Issue 03 , September 2012, , Pages 199-204

  Since most common form of cervical cancer starts with pre-cancerous changes, a flawless detection of these changes becomes an important issue to prevent and treat the cervix cancer. There are 2 ways to stop this disease from developing. One way is to find and treat pre-cancers before they become true ...  Read More