Seiki Yoshimori

Classification of hand postures based on 3D vision model for human-robot interaction

In this paper, a method for hand posture recognition, which is robust for hand posture changing in an actual environment, is proposed. Conventionally, a data glove device and a 3D scanner have been used for the feature extraction of hand shape. However, the performance of each approach is affected by hand posture changing. Therefore, this paper proposes the posture fluctuation model for efficient hand posture recognition, based on 3D hand shape and color feature obtained from a stereo camera. A large set of dictionary for posture recognition is built by various leaned hand images which were auto-created from one scanned hand image, based on plural proposed models. In order to show the effectiveness of proposed method, performance and processing times for posture recognition are compared to conventional method. In addition, we perform the evaluation experiment by using the Japanese sign language.

License Plate Detection Using Hereditary Threshold Determine Method

License plate recognition is very important in an automobile society. Also in it, since plate detection has big influence on subsequent number recognition, it is very important. However, it is very difficult to do it, because a background and a body color of cars are similar to that of the license plate. In this paper, we propose a new thresholds determination method in the various background by using the real-coded genetic algorithm (RGA). By using RGA, 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 RGA to estimate thresholds function by using the recursive least squares (RLS) algorithm. Finally, in order to show the effectiveness of the proposed method, we show simulation examples by using real images.

License plate detection system in rainy days

License plate recognition is very important in an automobile society. However, it is very difficult to do it, because a background and a body color of cars are similar to that of the license plate. Furthermore, the detection of cars in a moving at a very high-speed is difficult to be done. In this paper, we propose a new robust thresholds determination method in the various background by using the real coded genetic algorithm (RGA). By using RGA, 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 recursive least squares algorithm. Finally, in order to show the effectiveness of the proposed method, we show simulation examples by using real images.

A design of the object detection system using the RGA

License plate recognition is very important is an automobile society. However, it is very difficult to do it, because the background and body color of cars are sometimes similar to that of the license plate. Furthermore, the detection of cars moving at a very high speed is difficult. In this paper, we propose a new robust thresholds-determination method in various backgrounds by using the real coded genetic algorithm (RGA). By using RGA, 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 recursive least squares (RLS) algorithm. Finally, in order to show the effectiveness of the proposed method, we show simulation examples by using real images. The resulting rate of detection is 85.0%.

Invisible Calibration Pattern Based on Human Visual Perception Characteristics

In the print-type steganographic system and watermark, a calibration pattern is arranged around contents where invisible data is embedded, as plural feature points corresponding to between an original image and the scanned image for normalization of the scanned image. However, it is clear that conventional methods interfere with page layout and artwork of contents. In addition, visible calibration patterns are not suitable for security service. In this paper, we propose an arrangement and detection method of an invisible calibration pattern based on characteristics of human visual perception. The calibration pattern is embedded to blue intensity in an original image by adding high frequency component.

INVISIBLE CALIBRATION PATTERN FOR PRINT-AND-SCAN DATA HIDING BASED ON HUMAN VISUAL PERCEPTION

In print-type steganography and watermarking, visible calibration patterns are arranged around content in which invisible data are embedded, to provide plural feature points for normalization of a scanned image. However, it is clear that conventional visible calibration patterns interfere with the page layout and artwork of original contents. Additionally, visible calibration patterns are not suitable for security services. In this paper, we propose an arrangement of and a detection method for an invisible calibration pattern based on human visual perception. We embed the proposed calibration pattern in an original image by adding a high-frequency component to blue intensity in limited regions. The proposed method protects the page layout and artwork because it is difficult for observers to detect the calibration pattern embedded into an image with a normal background.

A proposal of feature extraction for impression analysis

The concern of image processing has increased, in recent year. However, the evaluation of facial impression that we are naturally doing from ones face in our daily life is not treated in this area. The automatic facial impression evaluation applies for wide area. Then we analyzed important facial featres for impression analysis, in order to achieve automatic evaluation of facial impression. In order to evaluate the proposed method, we performed computer simulation. As the result of this simulation, we confirmed that important facial features for facial impression are differece while gender and age.

An Important Facial Parts Analysis for Evaluating the Impression - Difference by Gender

The concern for image processing has increased very much, in recent year. However, the evaluation of facial impression is not treated in this area that we are naturally doing in our daily life to see an ones face. Wide ranges of applications are released from the achievement of the impression automatic evaluation. Then we analyze important facial parts for impression analysis, in order to achieve automatic evaluation of facial impression. In order to analyze the important facial parts, we performed computer simulation. As the result of this simulation, difference of important areas by gender that relate impression words were detected.

A proposal of adaptive graininess suppression method

Previous studies of image restoration for noise image were based on mask processing. These conventional noise removal methods represented from mask processing have issue of definition degradation to accompany spacial processing. In this paper, we propose a graininess suppression method based on edge shape. In this method, we detect edges from a noise image and perform graininess suppression for this image based on edge information. On the edge detection, we execute an image transformation for an image that enables us to extract edge by making principal component image. Moreover, we use the canny edge detection operator that can detect a weak edge that relates to a real edge, and do not detect a lie edge. In the suppression process, we use Wiener filter that can restore an noise image without making a complete edge map and the original signal map. We have that the present method for the noise added images to verify effectiveness and have confirmed this.

Object Extraction System by Using the Evolutionaly Computations

License plate recognition is very important in an automobile society. However, it is very difficult to do it, because a background and a body color of cars are similar to that of the license plate. Furthermore, the detection of cars in a moving at a very high-speed is difficult to be done. In this paper, we propose a new robust thresholds determination method in the various background by using the real coded genetic algorithm (RGA). By using RGA, 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 recursive least squares (RLS) algorithm. Finally, in order to show the effectiveness of the pro-posed method, we show simulation examples by using real images, and result rate of detection is 85.0%.