Methods Of Image Compressions

1200 Words5 Pages
ce this method depends on the centre mass of the object, the generated images have different sizes [5], for this reason a scaled normalization operation are applied to overcome this problem which maintain image dimensions and the time as well [5], where each block of the four blocks are scaling with a factor that is different from other block’s factors. Two methods are used for extraction the features; firstly by using the edge mages, and secondly by using normalized features where only the brightness values of pixels are calculated and other black pixels are neglected to reduce the length of the feature vector [5]. The database consists of 6 different gestures, 10 samples per gesture are used, 5 samples for training and 5 samples for…show more content…
The drawbacks of some discussed methods are explained: Orientation histogram method applied in [19] have some problems which are; similar gestures might have different orientation histograms and different gestures could have similar orientation histograms, besides that, the proposed method achieved well for any objects that dominate the image even if it is not the hand gesture [19]. Neural Network classifier has been applied for gestures classification[8] but it is time consuming and when the number of training data increase, the time needed for classification are increased too [8]. In [2] the NN required several hours for learning 42 characters and four days to learn ten words [2]. Fuzzy c-means clustering algorithm applied in [6] has some disadvantages; wrong object extraction problem raised if the objects larger than the hand. The performance of recognition algorithm decreases when the distance greater than 1.5 meters between the user and the camera. Besides that, its variation to lighting condition changes and unwanted objects might overlap with the hand gesture. In [16] the system is variation to environment lighting changes which produces erroneous segmentation of the
Open Document