Abstract: A three-dimensional shape modeling of a real object that reduces the limitations on the target shape and color. The rough shape of the target object is determined by a silhouette method (which has limitation on the target shape) and, at the same time, the detailed shape of the target object is determined by a triangulation method or the like (which has limitation on the target color). By using both sets of information, the consistency between the rough and detailed shape information are checked. For the portions where the consistency is not satisfied (points where detailed shape information is absent or points where detailed shape section is present outside the rough shape), rough shape is assumed to be the final object information and for other portions, the detailed shape is taken as the final object information. In this manner, three-dimensional shape modeling with reduced limitations on the target shape and color can be performed.

Abstract: A method for improving disease diagnosis using contrast enhancement presentation comprising: providing an input digital diagnostic image; applying a decomposition filter bank to the input digital diagnostic image; constructing a tone scale curve from the input digital diagnostic image; applying said tone scale curve to the input digital diagnostic image to produce a tone-scaled image; applying a decomposition filter bank to the tone-scaled image; generating the contrast weight control signals from the input digital diagnostic image by extracting the high contrast edge signals at the coarse scale; adjusting the decomposition outputs from both the input image and the tone-scaled image according to the contrast weight control signals; and applying a reconstruction filter bank to the adjusted signals to produce a contrast enhancement presentation output image.

Abstract: A method for compressing an intensity dynamic range of an input image to a reduced intensity dynamic range of an image display device includes defining a plurality of units of the input image, determining a local mean estimate of an intensity of each of the plurality of units of the input image, generating a contrast modification processing value for each local mean estimate, and generating an output intensity value, for each local mean estimate, by using only the generated contrast modification processing value and an input intensity value.

Abstract: In video signal processing, diagonal lines or slopes are detected in the input material, and an adaptive spatial filter having positive, negative and linear filter apertures is employed. The positive filter aperture is employed upon detection of any positive slopes in excess of a defined positive threshold; the negative filter upon detection of negative slopes, and the linear filter otherwise.

Abstract: The present invention is directed to solving the problems associated with the detection of surface defects on metal bars as well as the problems associated with applying metal flat inspection systems to metal bars for non-destructive surface defects detection. A specially designed imaging system, which is comprised of a computing unit, line lights and high data rate line scan cameras, is developed for the aforementioned purpose. The target application is the metal bars (1) that have a circumference/cross-section-area ratio equal to or smaller than 4.25 when the cross section area is unity for the given shape, (2) whose cross-sections are round, oval, or in the shape of a polygon, and (3) are manufactured by mechanically cross-section reduction processes. The said metal can be steel, stainless steel, aluminum, copper, bronze, titanium, nickel, and so forth, and/or their alloys. The said metal bars can be at the temperature when they are being manufactured.

Abstract: Image dividing means of an RPU divides raw image data into divided image data A1 having 2048 horizontal pixels and A2 having 1024 horizontal pixels. The divided image data A1 is continuously processed in single pixel processing means and multiple pixel processing means and thereafter transferred to and stored in a buffer. The divided image data A2 is processed in the single pixel processing means and thereafter transferred to and temporarily stored in another buffer. The multiple pixel processing means reads and processes divided image data A2a stored in this buffer and thereafter transfers and stores the same to and in still another buffer. Image combining means reads divided image data A1b and A2b stored in the buffers and combines the same with each other. Thus, an image processing time and a cost can be reduced even if raw image data having horizontal pixels in a number exceeding the capacity of a line memory is received.

Abstract: Control points used in deriving an object boundary for a prior frame are overlaid onto a current frame. An initial estimate of an object boundary are derived from the control points and edge energy data. The operator adjusts the control points to better model the boundary for the current frame. For each updated control point, the object boundary is rederived. A restricted area is defined encompassing the initial control points. When a control point is moved outside the restricted area, the restricted area is redefined to accommodate it. The boundary between control points is derived by finding a best path. Only points within the restricted area are considered. A first set of rules is used to find the best path when the distance between the two points is less than threshold value. A second set of rules is used when the distance between the two points exceeds the threshold value.

Abstract: Methods, data, and systems are provided to warp an image. Input pixels associated with an input image are warped according to a provided or obtained warping function. A single weight is assigned to each input pixel. The weight represents each input pixel's horizontal and vertical dimensions within an output lattice. The single weight is combined with an intensity value associated with each input pixel to map each input pixel to the output lattice in a single processing pass.

Abstract: A method of spatially filtering a digital image includes receiving a source digital image including pixels corresponding to one or more different colors; selecting a pixel of interest in the source digital image; calculating two or more noise free pixel estimates for the pixel of interest using pixel values sampled in a local region about the pixel of interest; selecting a final noise free pixel estimate for the pixel of interest from the noise free pixel estimates; and repeating for other pixels in the source digital image to provide a spatially filtered digital image.

Abstract: The present invention relates to a data processing method, which data are included in an incoming digital image. This method comprises a calculation step (ACT) of a spatial activity value of a current pixel based on values (Y) of said current pixel and pixels adjacent thereto, a determination step (NND) of a non-natural uniform area (NN) if the spatial activity value of various consecutive pixels is lower than a first predetermined threshold value. The invention also includes a gradient filter step (GF) of values (Y) of the pixels adapted to detect (THR1) strong edges (SE) inside the image and a detection step (RD) of a ringing artifact. The invention finally comprises a filter step (FIL) of values (Y) of the pixels comprised in a filtering area which is located between a non-natural uniform area (NN) and a strong edge (SE) which are close together and where at least a ringing artifact has been detected.

Abstract: A method of removing streaks from multi-band digital images is presented in which a multi-band image is transformed to an advantageous spectral space, in which a streak removal operation is applied to the image in the advantageous spectral space. The streak removal operation is a method of removing columnar streaks from a multi-band digital image of the type in which it is assumed that pixels in a predetermined spatial and spectral region near a given pixel are strongly related to each other and employing gain and offset values to compute streak removal information, a test is performed for a strong relation between the pixels in a predetermined region spatially and spectrally near a given pixel and streak removal information is computed only if such a strong relationship exists, whereby image content that does not extend the full length of the image in the column direction will not be interpreted as a streak.

Abstract: A pixel processing system receives a target pixel value and neighbor pixel values. The neighbor pixel values may correspond to eight neighbor pixels that surround a target pixel corresponding to the target pixel value. The pixel processing system determines a minimum value and a maximum value among the neighbor pixel values. If the target pixel value is less than the minimum value, then the pixel processing system increases the target pixel value. If the target pixel value is greater than the maximum value, then the pixel processing system reduces the target pixel value. In response to increasing the target pixel value, the pixel processing system may reduce the neighbor pixel values to maintain an average value. In response to reducing the target pixel value, the pixel processing system may increase the neighbor pixel values to maintain an average value.

Abstract: An example-based facial sketch system and process that automatically generates a sketch from an input image depicting a person's face. Sketch generation is accomplished by first training the system using example facial images and sketches of the depicted faces drawn with a particular style by a sketch artist. The trained system is then used to automatically generate a facial sketch that simulates the artist's style from an input image depicting a person's face. Nonparametric sampling and a flexible sketch model are employed to capture the complex statistical characteristics between an image and its sketch.

Abstract: In a method for compensating for pattern distortion of sheet-type work material spread onto a support surface a processing apparatus is provided and carries said support surface. The work material is spread onto the support surface and images of selected areal portions of the work material are captured. A controller analyzes these images and projects them onto a display whereupon the images are mapped to define any distortion in the work material. The controller then undistorts the images of these areal portions and projects them back onto the display so that an operator can position undistorted digital representations of pattern pieces onto the undistorted images of the work material. The controller then distorts the geometry of the pattern pieces positioned on the work material by the operator to conform to the distortion in the spread material.

Abstract: A method of calculating a noise characteristic value for a source digital image includes receiving a source digital image including pixels corresponding to two or more different colors; using pixel values corresponding to a first color to produce at least one color correlation term for pixels corresponding to a second color which respectively indicate the extent of the noise content in the pixel values of the second color; and using the color correlation term to calculate a noise characteristic value for the pixels corresponding to the second color.