In this paper, a new image restoration approach using the Akamatsu transform is presented. In the method, by using repeated simple calculations based on the Akamatsu transform, an out-of-focus blurred image can be restored and sharpened. Out of focus is a major problem bothering many people in photography, especially the amateurs. There exits some solution to this problem on both the hardware and software sides. However, none offers a perfect solution. The Akamatsu transform can easily be embedded into hardware to offer faster processing due to its simplicity. Although, initially proposed for speech processing, this paper show the effectiveness of the transform in image processing. The Akamatsu transform is a combination of integral and differential transforms. The algorithm can be effective tools for image restoration in realtime image processing.
SUMMARYThis paper presents a method for gender and age estimation which is robust to changing facial pose. We propose a feature point detection method, called the adapted retinal sampling method (ARSM), and a feature extraction method. A basic concept of the ARSM is to add knowledge about the facial structure to the retinal sampling method. In this method, feature points are detected on the basis of seven points corresponding to facial organs from a facial image. The reason why we used seven points as the basis of feature point detection is that facial organs are conspicuous in the facial region, and are comparatively easy to extract. As features robust to changing facial pose, skin texture, hue, and the Gabor jet are used for gender and age estimation. For classification of gender and estimation of age, we use a multilayered neural network. We also examine the left-right symmetry of faces in connection with gender and age estimation by the proposed method.
Cukumi@is.tokusbima-mac. in pedrycz@ee.alberta.ca akamatsu@is.tokushima-u.ac.jp minow@is.tokushima-u.ac.jp mitsue@cc.okayama-u.ac.jp Absh-act -License plate recognition is very important in an automobile society. However, it is very difficult to do it, because a background and a car surface color can be similar to that of the license plate. Furthermore, detection of cars moving at a very high-speed is difficult to be done. In this paper, we propose a new method to extract a car license plate automatically by using a genetic algorithm (CA). By using CA, the most likely plate colors are decided under various light conditions. First, the average brightness Y values of images are calculated. Next, relationship between the Y value and the most likely plate color thresholds (upper and lower bounds) are obtained by GA to estimate threshold equations by using the RLS algorithm. Finally, in order to show the effectiveness of the proposed method, we show simulation examples by using real images. I. INTRODUCnON 0-7803-8376-
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