In vitro fertilization – a procedure which aims to get the embryo to adapt the methods of "oocyte" fertilized sperm outside the human body. At the end of this procedure there are several embryos. This paper represents overview of tracking-free and tracking-based methods for detection of important embryo development stages. Tracking-based method represents well known classical object tracking techniques. For tracking-free method were selected statistical feature extraction techniques and classification methods: Classification with training and classification without training. For the feature extraction proposed statistical methods: entropy, invariant moments and principal components analyses. For the classification are used neural networks, support vector machine and K-nearest neighbor method. Data collected consist of 500 images for each class. 70 percent of images are dedicated for training, and 30 percent for testing. The proposed method is checked by experiment. It is expected that this method will work well in video sequences.
APPLICATION OF NUMERICAL INTELLIGENCE METHODS FOR THE AUTOMATIC QUALITY GRADING OF AN EMBRYO DEVELOPMENT