A new face detection system is presented. The system combines several techniques for face detection to achieve better detection rates, a skin colormodel based on RGB color space is built and used to detect skin regions. The detected skin regions are
the face candidate regions. Neural network is used and trained with training set of faces and non-faces that projected into subspace by principal component analysis technique. we have added two modifications for the classical use of neural networks in face detection. First, the neural network tests only the face candidate regions for faces, so the search space is reduced. Second, the window size used by the neural network in scanning the input image is adaptive and depends on the size of the face candidate region. This enables the face detection system to detect faces with any size.
Orange fruits are characterized at harvesting with physical and sensory
properties determine consumer acceptance and in order to identify these
characteristics and vulnerability storage and irradiation conditions, Valancia
orange fruits were subje
cted to gamma irradiation at doses of 0.0, 0.5, 1.0, and
1.5 kGy using gamma 60Co irradiator facility. Fruits were kept in a refrigerator
for 18 weeks. Results indicated that physical and sensory properties of Valencia
orange fruits were affected by storage time and irradiation. The overall color
differences were increased and the firmness of fruits and skin were decreased.
The used doses of gamma irradiation increased the overall color differences of
fruit skin. Whereas the fruit firmness, and the sensory properties (aroma,
color, test and firmness) of irradiated Valencia orange fruits were decreased.
