Creating a Database for Wide-Close-Normal Eyes

In this stage, we are trying to classify different eyes shapes. The most important thing in this classification is distance between of two eyes. For example, if the space between two eyes is smaller than the width of one eye, this is close set eye or if vice versa, this is wide set eye. For normal set eyes, we specified a tolerance value and tested over approx. a hundred images. Then, we classified these images which called wide-close- normal eyes. In next stage, we will try in our program each image and make a histogram to get a correct result for classification.

For instance this is close set eyes.

Normal Set Eyes

Wide Set Eyes

Close Set Eyes

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Simple Eyes Classification

There are lots of multiple kind of eyes on people. We can`t understand which kind of eyes at first view. In this samples, we will show you how to detect type of eyes. Even if there are a lot of variable eyes, firstly we will try to simple classification. We will consider only 3 types of eyes which are CAT EYE, OVAL EYE, DROOPY EYE. We shouldn`t try to low definition images to get accurate results. 1. CAT EYE 2. ROUND/OVAL EYE 3. DROOPY EYE

Iris Detection on Faces

If you want to find a distance between two eyes or two eyelids in mm, you can have difficult in this. Because, you can measure iris in pixel but you can't in mm. You need have a reference. So, we chose iris as a reference point. The reason of selecting iris is all people have mostly same iris diameter which is 11,8 mm. So, we tried to detect iris on human faces. Firstly, we cropped eyes on each face photo and carried out circle detection. Here are some results.

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