Abstract: A mobile object combination detection apparatus includes a plurality of moving image input units, a plurality of mobile object detection units each connected to one of the moving image input units, and a combination determination unit. Each of the plurality of mobile object detection unit detects a mobile object at a predetermined position on a moving image inputted thereto from the moving image input unit, and sends detection information to the combination determination unit. The combination determination unit compares the detection information of the mobile object sent thereto from each of the mobile object detection unit with a predetermined condition to determine that a target mobile object is detected-when the detection information satisfies the predetermined condition.

Abstract: A method for processing partial lines of image data from a detector, each partial line of data representing a portion of an image pixel matrix, includes: (a) communicating partial lines of image data over a network from an imaging system to a remote facility; (b) receiving partial lines of image data in a first sequence; (c) assigning to each partial line of image data in a first series a position in a second sequence by reference to a plurality of base addresses; (d) altering the base addresses; and (e) assigning to each partial line of image data in a second series a position in the second sequence by reference to the altered base addresses.

Abstract: A method for generating on demand a gray scale transfer curve for use in displaying an image comprised of a plurality of digital values representing pixel gray scale levels with a desired contrast and brightness. This is achieved by using a single sigmoid shaped function Y=f(X, a, b, c) resembling an H&D curve of a photographic film. The Y axis represents digital output values to be used in displaying an image, while the X axis represents input digital values representing captured image information. “a” is a number representing boundary conditions for X and Y, “b” is a first parameter controlling the location of the curve along the X axis and “c” is a second parameter controlling the slope of the curve slope. This function is used to derive a Look-Up-Table (LUT) representing a continuous GST curve having the desired contrast and brightness.

Abstract: In a computerized method, a moving articulated figure is tracked in a sequence of 2-D images measured by a monocular camera. The images are individually registered with each other using a 2-D scaled prismatic model of the figure. The 2-D model includes a plurality of links connected by revolute joints to form is a branched, linear-chain of connected links. The registering produces a state trajectory for the figure in the sequence of images. During a reconstructing step, a 3-D model is fitted to the state trajectory to estimate kinematic parameters, and the estimated kinematic parameters are refined using an expectation maximization technique.

Abstract: An early tumor detection method based on the coherent superposition of a medical MRI or CAT scan digital images. A first digital image to be superimposed on a second digital image is translated and rotated to minimize mean quadratic error between the images. An optimal lowpass vector field is then calculated which, when applied to the translated and rotated digital image, further reduces the quadratic error between the images. Next, an optimal highpass vector field is calculated such that when it is subtracted from said lowpass vector field, and the resulting vector applied to said first digital image, both the first and second digital image are superimposed to a high degree of correlation. Finally, the divergence of the high-wave vector part of resulting reduced vector field is calculated and regions of either negative or positive divergence representative of potential malignant tumor growth are displayed for a medical specialist to view.

Abstract: For two-dimensional processing of spotlight SAR data into exact image data, the spotlight SAR raw data are divided into azimuth sub-apertures and transformed into the range-time/azimuth-frequency domain through short azimuth FFTs. The obtained data are multiplied by a frequency-scaling function Hf(fa, tr; r0) and transformed into the two-dimensional frequency domain through short range FFTs, multiplied by an RV-phase-correction function HRVP(fr) and subsequently transformed back into the range time/azimuth-frequency domain through short range IFFTs. The data formed in this manner are multiplied by the inverse frequency-scaling function Hg(fa, fr), then transformed back into the two-dimensional frequency domain, multiplied by the phase-correction function Hkorr(fa, fr) and the azimuth-scaling function Ha(fa, fr), and transformed back into the range-frequency/azimuth-time domain through short azimuth FFTS.

Abstract: In a method of detecting covered and uncovered parts in an image to be interpolated between neighboring previous (I) and next (III) input images, backward motion vectors from the next input image to the previous input image, and having corresponding backward estimation errors, and forward motion vectors from the previous input image to the next input image, and having corresponding forward estimation errors, are determined, uncovered and covered parts are detected in the neighboring previous and next input images, respectively, in the thus detected uncovered parts, uncovered parts in the image to be interpolated are detected by determining second backward estimation errors by comparing both neighboring previous and next input images when partially shifted over the backward motion vectors to a temporal location of said image to be interpolated, and by comparing the second backward estimation errors to a threshold, and in the thus detected covered parts, covered parts in the image to be interpolated are detecte

Abstract: A method (300) of characterizing a lithographic scanning system includes the steps of printing a first pattern (302) using a reticle (220) having a first orientation with respect to the lithographic scanning system and measuring a critical dimension of the first pattern at a plurality of points (310). The method (300) further includes printing a second pattern (320) using the reticle (220) having a second orientation with respect to the lithographic scanning system different than the first orientation and measuring a critical dimension of the second pattern at the plurality of points (322).

Abstract: A manufacturing system including: (a) a vessel for holding a liquid; (b) a first member and a second member, each having a flat surface, wherein the flat surface of the first member faces and is spaced from the flat surface of the second member, thereby defining a gap region between the two flat surfaces, wherein a section of the first member is transparent through the thickness of the first member; (c) a liquid delivery system connected to the vessel and the gap region which delivers the liquid to the gap region and the liquid flows in the gap region in view of the transparent section of the first member; (d) a camera positioned to view through the transparent section of the first member; (e) image processing means coupled to the camera for determining the homogeneity of the liquid in the gap region; and (f) liquid dispensing equipment connected to the liquid delivery system.

Abstract: Systems and method for organizing information relating to the design of polymer probe array chips including oligonucleotide array chips. A database model is provided which organizes information interrelating probes on a chip, genomic items investigated by the chip, and sequence information relating to the design of the chip. The model is readily translatable into database languages such as SQL. The database model scales to permit storage of information about large numbers of chips having complex designs.

Abstract: Each of the N surface images, used to restore the borehole or the core sample surface image, is segmented into related components (C(12), C(11), . . . ) Which are grouped into related regions (C(8)), each touching both the right and left edges of the image. After smoothing out their contours, the related regions are represented in the form of an image, called bed image, representative uftlle stratification beds. The contours appearing on the N bed images are matched to construct the bed boundary sinusoidal curves. This is particularly useful in determining stratification of a geological site.