• Saroja Ramachandra
• Keertana Vinod Ram
• Poojitha Narayan
• Sudesh V Rokade
• Shruthi B

This paper uses image processing and data mining methods to develop an automatic image recognition system for woman's ovulation prediction. Detecting woman's ovulation can help fertility check, especially for woman who are conditioned to PCOD and abnormal thyroid levels ,diagnosis certain diseases and helps avoid undesired pregnancies. Saliva ferning test is a technique that monitors woman's saliva and looks for fern patterns which indicates ovulation. This involves the use of a digital camera with a 100x microscope to take saliva images and study them [2]. In the proposed method, important features in dried saliva images are automatically extracted by employing some image processing techniques which is then classified based on the density of the ferns, alongside measuring the basal body temperature of the subject in continuous intervals during the night and plotting the characteristics, an abnormal drop or discrepancy in the temperature shows the commencement of the ovulation period [3]. This system which uses two parameters and combines the results of the two increases the accuracy of the prediction. This methodology has a lot of importance in economical, medical and human aspects. In addition, this system can detect woman’s ovulation period non-invasive, more safely, naturally and in a convenient and efficient manner.

Ovulation, Pattern Recognition, Fern Pattern, Basal Body Temperature

"A Novel Technique to Detect Ovulation by Digital Image Analysis of Salivary Fern Pattern and Core Body Temperature", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.110-113, May-2019, Available :http://www.jetir.org/papers/JETIRBM06017.pdf

"A Novel Technique to Detect Ovulation by Digital Image Analysis of Salivary Fern Pattern and Core Body Temperature", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp110-113, May-2019, Available at : http://www.jetir.org/papers/JETIRBM06017.pdf