Random noise injures both the basic image quality and also the following image processing procedures. The low-pass filter is commonly used as the image denoising. Low-pass filter can reduce noise; however, the edge becomes always blur as the side effect. In order to suppress this side effect, we proposed edge preserving noise reduction filter using Fast Mestimation method. As the Proposed method is applied experimentally to the noisy image, it was clarified that the noise was clearly reduced and the performance of edge preserving was realized at the same time. In this study, a quantitative evaluation of the denoising performance of the proposed method is obtained by varying the amount of noise applied and obtaining the denoising ratio.
The vanishing point detection technology helps automatic driving. In this study, the straight lines on a road for the clue of the vanishing point are extracted efficiently by using the regional division and angle limitation. And, the vanishing point is detected robustly by using the fast M-estimation method. Proposed method could detect straight line ingredient tied to the vanishing point detection efficient on the road. And the vanishing point was detected exactly by the effect of the fast M-estimation method when the straight line ingredient which was not tied to the vanishing point detection was detected.
It is very important to guarantee the quality of the industrial products by means of visual inspection. In order to reduce
the soldering defect with terminal deformation and terminal burr in the manufacturing process, this paper
proposes a 3D visual inspection system based on a stereo vision with single camera.
It is technically noted that the base line of this single camera stereo was precisely calibrated by the image processing
procedure. Also to extract the measuring point coordinates for computing disparity; the error is reduced with original
algorithm. Comparing its performance with that of human inspection using industrial microscope, the proposed 3D
inspection could be an alternative in precision and in processing cost. Since the practical specification in 3D precision
is less than 0.02 mm and the experimental performance was around the same, it was demonstrated by the proposed system
that the soldering defect with terminal deformation and terminal burr in inspection, especially in 3D inspection,
was decreased.
In order to realize the inline inspection, this paper will suggest how the human inspection of the products could be
modeled and be implemented by the computer system especially in manufacturing process.
We propose a method for quantifying the design of automotive frontal view based on the research on the human visual
impression to the facial expression. We have researched to evaluate the automotive frontal face by using the facial
words and the perceived age. Then we verified experimentally how effectively the line drawing image could work and
coche-PICASSO image could be used for the image stimulation. As a result of this paper, a part of the facial words
could be strongly correlated to both the facial expressions and the perceived age in the line drawing image. Besides, it
was also known that the perceived age in the coche-PICASSO image was always younger than those of the line drawing image.
KEYWORDS: Quantization, Digital imaging, Fourier transforms, Image processing, Scanning electron microscopy, Image restoration, Probability theory, Digital image processing, Image compression, Analog electronics
OK-Quantization Theory for the digitization in value ensures the reconstructivity of the probabilistic density function of the image. This paper shows some experimental demonstrations to reduce the number of the gray levels, and shows mainly that there is a necessary analytical relationship between sampling and quantization based on the equivalence relationship between two kinds of the integral, Riemann and Lebesgue integrals for calculating the volume of the image. Experimental demonstrations are also shown in this paper.
Since, at our laboratory, the basic configuration of the facial caricaturing system PICASSO has been constructed, it is strongly expected to get sufficient input image from a person who is naturally performing in front of the PICASSO camera system. From this viewpoint, we developed a face tracking PC system for capturing sufficient facial image especially in size by means of PTZ (Pan-Tilt-Zoom) camera collaborated with a fixed CCD camera. Irises are successfully recognized from the motion images captured from PTZ camera. These irises can be utilized to provide a key feature for realizing an automated facial recognizing system. In this system, a person performing naturally in pose and in facial expression within the scope of the fixed CCD camera can be stably tracked and the sufficient images in resolution of PTZ camera were successfully analyzed for iris recognition and facial parts extractions. This face tracking and face recognition system was characterized by a novel template replacement scheme among the successive image frames. Experimental results were also demonstrated in this paper. This system works well in a practical speed 6-9fps on a usual PC connected to these cameras.
We developed the facial caricaturing robot "COOPER", that was exhibited at the Prototype Robot Exhibition of EXPO 2005, Aichi Japan during 11 days from Jun.9 to Jun.19. COOPER watches the face of a person seated at the chair, obtains facial images, and analyzes the images to extract 251 feature points to generate his facial line drawings with deformation. It is noted that the caricature was drawn on the specialized "Shrimp rice cracker" in 4 minutes. To do this we customized the original system PICASSO by coping with the illumination circumstances in EXPO pavilion. This paper illustrates the outline of the COOPER and the details of the image processing in it. And we discusses on the prospects of the future subjects based on more than 395 facial caricatures obtained at EXPO2005.
We demonstrate a real time 3D position sensing of multiple light sources by capturing their ring images that are transformed by the molecular lens system with large spherical aberration. The ring images change in diameter in accordance with the distance to the light sources, and the ring center positions determine the directions toward them. Therefore, the 3D positions of light sources are calculated by detecting the diameters and center positions of the circles. This time we succeeded to measure 3D positions of multiple light sources simultaneously in real time by extracting and tracking the circle patterns individually. Each circle is extracted by the Hough transform technique that uses not-closely-distributing three edge points to search the primal votes more than threshold, and is tracked by predicting the successive positions by Kalman filter. These processes make it possible to measure the 3D positions of light sources even in the case of overlapped plural circles. In the experiment, we could track several circle patterns measuring the center positions and diameters, namely, measuring the 3D positions of LEDs in real space. Measurement error of 3D positions for a LED was 6.8mm in average for 150 sampling points ranging from 450mm to 950mm in distance.
Since, at our laboratory, the basic configuration of the facial caricaturing system PICASSO has been constructed, it is strongly expected to get sufficient input image from a person who is naturally performing in front of the PICASSO camera system. From this viewpoint, we developed a face tracking PC system for capturing sufficient facial image especially in size by means of PTZ (Pan-Tilt-Zoom) camera collaborated with a fixed CCD camera. Irises are successfully recognized from the motion images captured from PTZ camera. These irises can be utilized to provide a key feature for realizing an automated facial recognizing system. In this system, a person performing naturally in pose and in facial expression within the scope of the fixed CCD camera can be stably tracked and the sufficient images in resolution of PTZ camera were successfully analyzed for iris recognition and facial parts extractions. This face tracking and face recognition system was characterized by a novel template replacement scheme among the successive image frames. Experimental results were also demonstrated in this paper. This system works well in a practical speed 6-9fps on a usual PC connected to these cameras.
The goal of HUTOP project is to rearrange the technical subjects inherent in the Total Production Life Cycle (TPLC) and to model a new human-centered TPLC by introducing new information technologies (IT) which could support and enhance the KANSEI human sensory factors. HUTOP concept will be described again in this paper through the analysis of the basic research sub-themes in order to investigate the next international activities. Second phase of HUTOP was designed as HUTOP-II, and HUTOP-II research activities are now on going.
Mathematical basis for the digitization of gray value of the image is proposed. This can be called Oteru-Kochimizu's Quantization Theorem (OK-QT), just in the same meaning of Shannon's Sampling Theorem (Shannon-ST) for the digitization of the shape of the image. Inspired by the fact ST is the reconstruction theorem of the analog image from discrete image, OK-ST was modeled as the reconstruction theorem of the shape of the probability density function of gray value of the image. This is the novel and unique mathematical basis for the digitization of the gray scale of the image. This paper shows the outline of this theorem and shows also some experimental results to demonstrate its practical applicability. Through this, OK-QT gives a clue to the mathematical paradigm for the complete digitization basis, together with Shannon ST.
Since at our laboratory, the basic configuration of the facial caricaturing system PICASSO has been constructed, it is strongly expected to get sufficient input image from a person who is naturally performing in front of the PICASSO camera system. From this viewpoint, we developed a face tracking PC system for capturing sufficient facial image especially in size by means of PTZ (Pan-Tilt-Zoom) camera collaborated with a fixed CCD camera. Irises are successfully recognized from the motion images captured from PTZ camera. These irises can be utilized to provide a key feature for realizing an automated facial recognizing system. In this system, a person performing naturally in poise and in facial expression within the scope of the fixed CCD camera can be stably tracked and the sufficient images in resolution of PTZ camera were successfully analyzed for iris recognition and facial parts extractions. This face tracking and face recognition system was characterized by a novel template replacement scheme among the successive image frames. Experimental results were also demonstated in this paper. This system works well in a practical speed 6-9fps on a usual PC connected to these cameras.
Caricature is affected strongly by the attribute relationship between input face and mean face. This paper proposes a method of facial attribute classification by means of the statistics of many mean faces and an input face. These processes are made up by the estimation function of the input face and the attribute matrix which is defined by the distances of all feature points of the face and its variances. There should be many attribute matrices characterized by the different age and different gender set of faces. This proposal delivered the expected results enough for the automation of the mean face selection and clarification as the new caricature generation principle.
We proposed a method of 3D caricature generation which is based on the automatic extraction of the facial parts for the 3D facial image. This method is likely to suffer sometimes fatal degradations in the feature extraction caused by a variation of the head pose (Roll, Pitch and Yaw rotations). Therefore, we propose a method of head pose modification by estimating roll and yaw rotations which are based on the irises position extracted by Hough transform from texture image. We improved the quality of the mean face and the caricatures by this head pose estimation.
Face is the most effective visual media for supporting human interface and communication. We have proposed a typical KANSEI machine vision system to generate the facial caricature so far. The basic principle of this system uses the “mean face assumption” to extract individual features of a given face. This system did not provide for feedback from the gallery of the caricature; therefore, to allow for such feedback, in this paper, we propose a caricaturing system by using the KANSEI visual information acquired from the Eye-camera mounted on the head of a gallery, because it is well know that the gaze distribution represents not only where but also how he is looking at the face. The caricatures created in this way could be based on several measures which are provided from the distribution of the number of fixations to the facial parts, the number of times the gaze came to a particular area of the face, and the matrix of the transitions from a facial region to the other. These measures of the gallery’s KANSEI information were used to create caricatures with feedback from the gallery.
In this paper, we propose a new Hough transform algorithm, Least Median of Squares (LMedS) Hough transform, which uses the measure of the least median of squares as the basis to estimate lines. This means that LMedS Hough transform can provide a new measure for finding lines as an alternative to the majority standard of the ordinary Hough transform and, therefore, that LMedS Hough transform can detect lines in the same way as LMedS line fitting procedure. In addition to this, because this algorithm is constructed on the Hough transform paradigm, the basic properties of Hough transform such as noise robustness, multi-line detection and global line detection are inherited in LMedS Hough transform algorithm.
We have been developing an image processing method for the automatic inspection of electronic devices and implemented it on PC. And this system was already fabricated in the real production line for collecting the practical performance. 2D edge detection method for evaluating the surface recognition of the printed circuit board was proposed so far, and the validity was clarified. In this paper the outline of this system is firstly explained and the performance of this system is reported in detail. However, since some defects appear at the top surface of the mold cannot be detected even with a set of this 2D inspection procedure, new 3-dimensional inspection of the flatness of the mold top surface was introduced. Depth from Focus Method was implemented in order to enforce this system to cope with 3-dimensional defects. An image processing method for evaluating the flatness of the face of the device is now developed by analyzing this 3D image. Affine transformation is employed here to reduce the geometric distortions inherent in the given images.
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