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.
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.
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.
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