Seiji Hata

Visual inspection machine for solder joints using tiered illumination

We have developed a visual inspection machine for solder int defects of SMDS (Surface Mount Devices) mounted on PCBs (Printed Circuit Boards). The change of the intensity of the reflected light obtained by illuminating the soldered surface from different incident angles depends on the gradient of the soldered surface. We generate an images that represents this change of intensity and analyze this image to inspect the solder joint defects. In addition we report on an automatic generation program of the NC data for inspection.

Unpositioned Workpieces Handling Robot with Visual and Force Sensors

A robot which can handle unpositioned workpieces using a three-dimensional (3-D) vision sensor and a force sensor has been developed. It can pick up an unpositioned small connector and mount it correctly on a printed circuit board. This paper presents the robot system configuration and its operation

Color Quality Inspection Of Imaging Device

This paper describes an automated color defect inspection system of color imaging devices. The system uses color image processing technology, but does not use conventional primary color (R,G,B) components. In this system, two kinds of chrominance signals (R-Y, B-Y) are introduced to analyze color images. Newly developed color edge detection and color contrast calculation methods are used to detect and evaluate the color defects. Color contrast are calculated by analyzing the two dimensional chrominance signals scatterplot. Algorithms of color defect inspection and experimental results are presented.

Automatic line-shaped defect evaluation of solid-state imaging device

A method to evaluate quantitatively the faint line-shaped defect existing in the imaging signal of a solid-state imaging device has been developed. Classifying line-shaped defects into nondirectional ones for which the direction of the line defect cannot be specified and those of vertical direction, we investigate an evaluation algorithm for each of them and evaluate them by experiments. For nondirectional line defects, noticing that the line defects resemble straight line defects, line defects are detected within an image using Hough transformation. Next, computing the length and contrast of line defects as evaluation parameters, the degree of defect was evaluated. In the computation, efficient processing was attempted by making some additions to the processing method. As a result, detection and evaluation were achieved within a practically reasonable time. Taking into consideration vertical line defects and noticing that defect evaluations by human eye are different depending on frequency ranges of lines, defects of contrast in high-frequency range using data interpolation and contrast in low-frequency range using smoothing process were found and then the degree of defects by these contrasts was evaluated. Using the forementioned algorithm, a system was developed for automatic evaluation of line-shaped defects for experiment and compared with the traditional evaluation by human eye. As a result, good agreement was obtained and the line-shaped defects of a solid-state imaging device were evaluated automatically.

A Compact Image Processor And It' S Application

------The authors had developed several image processors and applied them to our production lines in the past several years. Summarizing these experiences, the authors haye developed next generation of a compact image processor , the W/R-2. The Wfl-2 is a very compact image processor which consists of three specially designed gate array LSIs for image processing. A flexible image processing software packages and an interactive image processing language, the FA-RASICfl, have been adopted to minimize the development effort of the application systems . The image processor is applied to a robot assembly cell for the flatpackaged IC and proved its efficiency.

A method to recognize 3-dimensional objects in real time.

This paper comprehensively presents a method to recognize 3-dimensional objects within one second. Slit light data from a range finder and gray scale image from a TV-camera are used jointly. First, by subtracting the background image from the background with slit light image, an image containing only, the slit light is obtained. ±0.3 pixel accuracy in fixing the slit line position in the image is obtained by using a statistical method. The extracting time is 200 ms. Then syntax analysis for labeling objects and extraction of contour lines from the gray scale image line is reported. The threshold for processing the gray scale image is decided automatically by making use of the slit light. At last, the method to reconstruct 3-dimensional data from 2-dimensional data is presented. The coefficients between picture coordinates (I, J) and a spacial coordinates (x, y, z) are calculated using a least squares method. Totally, 400 ms for all execution time and ±0.2 mm in accuracy, are obtained.