Abstract: A method and system for detecting the approaching of a target object into a monitoring zone wherein the target object is scheduled to enter the zone is provided. The method includes providing motion image data continuously taken as an image from the monitoring zone, initially setting a plurality of monitoring areas in an image plane of the monitoring zone on a track along which the target object moves, extracting the image data of these monitoring areas from the motion image data, detecting an image variation of the respective monitoring areas through the processing of the image data of the monitoring areas for each monitoring area and deciding, based on the detection sequence of the monitoring areas corresponding to a detected image variation, whether of not the target object approaches into the monitoring zone.

Abstract: A high-speed saturation converter for a color image, comprising first R, G, and B image memories for storing digital color image data separated into R, G, and B, matrix coefficient calculating CPU for calculating two types of matrix coefficients .alpha. and .beta. defined by the following equation based on given saturation conversion coefficient a:.alpha.=1+2a, .beta.=1-a;a processor for calculating R, G, and B components r*, g*, and b* of an identical pixel when saturation conversion S*=aS is performed with respect to vector S, in an RGB color space, of saturation components corresponding to R, G, and B components of the identical pixel in the first R, G, and B image memories, in accordance with the following matrix equation defined when an intensity before and after the conversion is constant: ##EQU1## and second R, G, and B image memories for storing the R, G, and B components r*, g*, and b* calculated by the processor means in a position of the corresponding pixel.

Abstract: In a feature data processing apparatus, one of two designated reference density vectors di and dj, to which a feature vector x corresponding to a feature element is closer, is determined from dij of the equation:dij=(di-dj).multidot.x-(di-dj)/2This value is calculated for all the combinations of two reference feature vectors di and dj selected from a reference feature vector group dk (k=0 to n-1), thereby obtaining classification data. The classification data is determined, using a logical formula or a reference table. An average value of the components is calculated from the classification data and the components of all the feature vectors. The above operation is repeated until the calculated average and the components of the reference density vector converge within a predetermined allowance, thereby precisely classifying feature data.

Abstract: An apparatus for detecting from first image data mark image data corresponding to a mark and having a first length in a first direction and a second length in a second direction perpendicular to the first direction in unit of pixels. The apparatus includes a differentiating processor, an adding processor and a controller. The differentiating processor executes differential operations for the first image data in response to first and second differential operation commands from the controller to obtain second and third image data and executes the differential operations for fourth image data in response to third and fourth differential operation commands from the controller to obtain fifth and sixth image data.

Abstract: An image processing apparatus for obtaining a shading image from a plurality of two-dimensional tomogram images includes a first obtaining section for obtaining a plurality of distance gradation images from the plurality of two-dimensional tomogram images and a second obtaining section for obtaining a distance image having density data is selected from the distance gradation image density data in units of pixels in gradation. The distance image has density data representing, in gradation, distances from a pre-designated area on a pre-designated plane to an object in gradiation. The image processing apparatus further includes a third obtaining section for obtaining a normal image having as density data normal vector components of the object from the distance image, and a fourth obtaining section for obtaining the shading image having as density data luminance data obtained from the density data of the normal image and direction data representing a designated direction from when the object is viewed.

Abstract: A first memory stores a divided three-dimensional binary image as image data j of p bits. A second memory, equal to the first memory in size, stores data k of q bits, representing the section number of a corresponding memory section of the first memory. A histogram computing circuit concatenates data j and data k and obtains a histogram for the concatenated data. A computing unit computes a marginal distribution of the three-dimensional image on the basis of the histogram. A data conversion unit converts the p bit data to a first data image. An adder unit obtains from the first image a second image representing the marginal distribution P(x,y). The computing unit computes a marginal distribution P(x) and a marginal distribution P(y) from the second image, and also computes the volume and center of gravity of the three-dimensional binary image.

Abstract: An image processing apparatus includes a 3-dimensional frame memory. The frame memory is made up of a plurality of memory planes which are logically stacked in a depth direction (Z direction) and are accessed independently. The apparatus also includes a memory controller which can access a plurality of memory areas of the frame memory. These memory areas can be located in any desired position in the depth direction, and can each have a desired number of bits in the depth direction, regardless of a bit length of image buses contained in the apparatus and connected to an image processor, and the memory controller. The image processor receives data through the image buses, logically operates the data and outputs it to the image buses. When in read mode, the memory controller converts the data read out from the memory areas of the frame memory into the type of data which can be transferred through the image buses.

Abstract: First and second images as stereoscopic images of an object are obtained. The second image is shifted by a value dx. Absolute values of differences between image data of the shifted image and the first image are calculated, thus obtaining a third image. The third image is subjected to average value filtering to obtain a fourth image. A fifth image which has the same size as that of the fourth image and has a maximum gray level in an initial state is prepared. Image data having a smaller value is selected from image data of the fourth and fifth images to obtain a sixth image. Absolute values of differences between image data of the sixth and fifth images are calculated, thus obtaining a seventh image having the calculated absolute values as image data. A ninth image which has the same size as that of the seventh image. When the gray level of the pixel of the sevength image is 0, an eighth image is obtained to have the image data of the ninth image.

Abstract: According to this invention, in image data A and B which are respectively constituted by pixel groups .SIGMA.A.sub.ij and .SIGMA.B.sub.ij consisting of N pixels A.sub.ij and B.sub.ij (N is a positive integer; i and j respectively indicate a row position and a column position), and in which density data A.sub.dij and B.sub.dij of the pixels are expressed by n(2m)-bit data (n and m are positive integers), designated 2m-bit portion a.sub.ij of each density data A.sub.dij of image data A is divided into upper m-bit portion a.sub.uij and lower m-bit portion a.sub.Lij. A histogram processor calculates .SIGMA.a.sub.ij .multidot.b.sub.ij between 2m-bit portions a.sub.ij and b.sub.ij using a histogram obtained by the upper or lower m-bit portion a.sub.uij or a.sub.Lij and designated 2m-bit portion b.sub.ij of each density data B.sub.dij of pixel group .SIGMA.B.sub.ij. An average can also be calculated by a calculation section using the histogram. Therefore, a covariance can be calculated at high speed.

Abstract: An image data operation processing apparatus having a controller for transferring specified image data and generating various processing commands in accordance with an operation command input from an external unit. The controller reads out the specified image data from a plurality of image memories for storing n-bit, image data, and outputs the readout data to an operation unit. The operation unit includes an image data processor capable of performing a linear combination operation and obtaining the absolute value of a difference, and a look up table unit. The look up table unit includes a table generator, a conversion processor for receiving image data, the total number of bits of which does not exceed a maximum of m bits (m is an integer satisfying 3n/2.ltoreq.m<2n) and for performing data conversion, and a table memory. The table generator generates a table in response to a table generation command from the controller and stores it in the table memory.