Facial emotions is way of communication through which human beings interact with each other [2]. Facial expressions plays an important role in human communication and also gives the idea of emotions. Emotion is defined as a psycho-physiological process which is associated with mood, personality and motivation [1]. It is a function of time, space and differ from person to person. Emotions plays a vital role in human communication which can be expressed as either verbally or non-verbally. In recent years, researchers are trying to improve all aspects of interaction between humans and computers especially in the area of human emotion recognition by observing facial expressions. The process of determining whether two faces are of the same person
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Due to the irregularities and high complexity of facial images, a lot of investigation is required in detection of an image. Images are widely used in security systems where it is used for human identification, remote conference etc. Although security cameras are placed everywhere for identification of the guilty person or reducing crimes in our day to day life still security systems need human supervision which causes the major drawback. So to solve the problem of face recognition Genetic Algorithm technique is used in facial detection application. Genetic Algorithms is a search technique inspired by Darwin Evolutionary Theory that uses some selection mechanism …show more content…
Then it is related to face to find the probability of the largest connected region. If this regions height and width greater than or equal to 50 and the ratio between height and width is 1 and 2, then this area may be considered as the face [1]. For detection of the face boundary, the image is converted to a binary image. Then the binary image is used to isolate the forehead from the face. This is done by horizontally and vertically scanning the image from the mid-point. The maximum width is calculated. The eyebrow region is reached if the new width is half of the previous maximum width. After this, the face is cropped from the forehead and its height is 1.5 multiplied with its width.
2.2 Boundary detection
To detect the boundary of the eye region it is important to first find middle positions between the two eyes. Then the upper and lower positions of the eyebrows are found. The pixels are scanned horizontally and vertically to find the lower and upper position of two eyebrows. The detection is lip is done by considering the lip box and calculating the distance between the forehead and eyes. Then the lower height of eyes and the upper height of the lip box is determined. Then, the RGB image is sliced according to the lip box and sobel edge detector is used for detecting the eye and the lip region [1] [2][3].
2.3 Image
Due to the irregularities and high complexity of facial images, a lot of investigation is required in detection of an image. Images are widely used in security systems where it is used for human identification, remote conference etc. Although security cameras are placed everywhere for identification of the guilty person or reducing crimes in our day to day life still security systems need human supervision which causes the major drawback. So to solve the problem of face recognition Genetic Algorithm technique is used in facial detection application. Genetic Algorithms is a search technique inspired by Darwin Evolutionary Theory that uses some selection mechanism …show more content…
Then it is related to face to find the probability of the largest connected region. If this regions height and width greater than or equal to 50 and the ratio between height and width is 1 and 2, then this area may be considered as the face [1]. For detection of the face boundary, the image is converted to a binary image. Then the binary image is used to isolate the forehead from the face. This is done by horizontally and vertically scanning the image from the mid-point. The maximum width is calculated. The eyebrow region is reached if the new width is half of the previous maximum width. After this, the face is cropped from the forehead and its height is 1.5 multiplied with its width.
2.2 Boundary detection
To detect the boundary of the eye region it is important to first find middle positions between the two eyes. Then the upper and lower positions of the eyebrows are found. The pixels are scanned horizontally and vertically to find the lower and upper position of two eyebrows. The detection is lip is done by considering the lip box and calculating the distance between the forehead and eyes. Then the lower height of eyes and the upper height of the lip box is determined. Then, the RGB image is sliced according to the lip box and sobel edge detector is used for detecting the eye and the lip region [1] [2][3].
2.3 Image