Behrouz N. Shabestari

Online industrial thermography of die casting tooling using dual-wavelength IR imaging

Recent advances in IR system technology coupled with significant reduction sin cost are making thermography a viable tool for on-line monitoring of industrial processes. This paper describes the implementation of a novel rugged thermal imaging system based on a dual-wavelength technique for a large intelligent process monitoring project. The objective of the portion described herein is to deploy a non-contact means of monitoring die cast tooling surface thermal conditions and analyzing the data in the context of the process monitor. The technical and practical challenges of developing such a non-contact thermal measurement system for continuous inspection in an industrial environment are discussed, and methods of resolving them are presented. These challenges include implementation of a wavelength filter system for quantitative determination of the surface temperature. Additionally, emissivity variations of the tooling surface as well as IR reflections are discussed. The primary issues that are addressed, however, are compensation for ambient temperature conditions and optimization of the calibration process. Other issues center on remote camera control, image acquisition, data synchronization, and data interpretation. An example application of this system, along with in-plant images and thermal data, is described.

Detection of Secondary Reflections Using Morphology

This paper discusses very simple but effective one-dimensional morphological techniques for the identification of primary and secondary peak locations associated with reflected light patterns from glass surfaces. A common optical technique for measuring glass thickness and related properties is to observe light reflected from the glass surfaces. Two reflections can be observed when an appropriate structured light source is used to illuminate a glass surface. A very bright primary reflection associated with the reflection from the front surface will be observed along with a much fainter secondary reflection from the back surface. The secondary reflection is difficult to detect reliably given the large difference in magnitude between the two peaks, the presence of noise, and the varying amounts of overlap between the two peaks that can occur. The methods described in the paper have been implemented successfully for two vision applications using images acquired using standard matrix and linear cameras. The signal is preprocessed using one-dimensional morphological and linear methods to normalize the background and remove noise. Further morphological operations are performed to identify the peaks associated with primary and secondary reflections.

Structured region growing and recognition algorithm for nondestructive evaluation

A novel syntactic region growing and recognition algorithm called SRG will be presented. The primary function of SRG algorithm is detection of structured regions of interest in given image. The recognition technique operates on regions elected features, it is a subject of the next paper. The SRG algorithm can be outlined as follows. Preprocessing is performed to isolate the kernels of potential regions. The first level regions are grown until the region transition are detected. Regions sharing the same transition boundary are merged. The second level regions are grown and merged if they are within the same transition boundary. Growing process is repeated as necessary until whole image or specified region of interest is covered. Features such as area, depth, and others, are computed for each level region and are used for recognition. The recognition is based on region features without regard to region level. The algorithm was designed for analysis of nondestructive evaluation images. In particular, it was successfully tested on x-ray images and on ultrasonic contact scan images of ceramic specimens for detection of microstructural defects. The results of these tests are included in the paper.

Using Gnu C to develop PC-based vision systems

The Gnu project has provided a substantial quantity of free high-quality software tools for UNIX-based machines including the Gnu C compiler which is used on a wide variety of hardware systems including IBM PC-compatible machines using 80386 or newer (32-bit) processors. While this compiler was developed for UNIX applications, it has been successfully ported to DOS and offers substantial benefits over traditional DOS-based 16-bit compilers for machine vision applications. One of the most significant advantages with Gnu C is the removal of the 640 K limit since addressing is performed with 32-bit pointers. Hence, all physical memory can be used directly to store and retrieve images, lookup tables, databases, etc. Execution speed is generally faster also since 32-bit code usually executes faster and there are no far pointers. Protected-mode operation provides other benefits since errant pointers often cause segmentation errors and the source of such errors can be readily identified using special tools provided with the compiler. Examples of vision applications using Gnu C include automatic hand-written address block recognition, counting of shattered-glass particles, and dimensional analysis.

Automatic gauging using a light-section microscope

This paper describes the development of a cost effective and reliable spacer inspection system for AC-plasma display panels. The system generates three dimensional profiles of spacers using a light-section microscope in conjunction with a PC-based vision system. Structured lighting is used in the light section microscope to provide a measure of spacer height. The system provides an economical way for 100% inspection of all spacers to improve display panel quality and yield.

Low-cost real-time automatic wheel classification system

This paper describes the design and implementation of a low-cost machine vision system for identifying various types of automotive wheels which are manufactured in several styles and sizes. In this application, a variety of wheels travel on a conveyor in random order through a number of processing steps. One of these processes requires the identification of the wheel type which was performed manually by an operator. A vision system was designed to provide the required identification. The system consisted of an annular illumination source, a CCD TV camera, frame grabber, and 386-compatible computer. Statistical pattern recognition techniques were used to provide robust classification as well as a simple means for adding new wheel designs to the system. Maintenance of the system can be performed by plant personnel with minimal training. The basic steps for identification include image acquisition, segmentation of the regions of interest, extraction of selected features, and classification. The vision system has been installed in a plant and has proven to be extremely effective. The system properly identifies the wheels correctly up to 30 wheels per minute regardless of rotational orientation in the cameras field of view. Correct classification can even be achieved if a portion of the wheel is blocked off from the camera. Significant cost savings have been achieved by a reduction in scrap associated with incorrect manual classification as well as a reduction of labor in a tedious task.

Stemware inspection system

The objective of the system is inspection of individual pieces of stemware for geometry defects and glass imperfections. Cameras view stemware from multiple angles to increase surface coverage. The inspection images are acquired at three stations. The first inspects internal glass quality, detecting defects such as chemical residue and waviness. The second inspects the rim, geometry of the stemware body and stem, and internal defects such as cracks. The third station inspects the stemware base for geometrical and internal defects. Glass defects are optically enhanced through the use of striped pattern back lighting combined with morphological processing. Geometry inspection is enhanced through the use of converging illumination at the second station, while the third station utilizes large field true telecentric imaging. Progressive scan cameras and frame grabbers capable of simultaneous image capture are used at each station. The system software comprises six modules: system manager, I/O manager, inspection module for each station, and stemware sorting and logging module. Each module is run as a separate application. Applications communicate with each other through TCP/IP sockets, and can be run in a multi-computer or single-computer setup. Currently two Windows NT workstations are used to host the system.

Design of a flexible image processing library in C

There are two crucial, complementary, issues faced during design and implementation of practically any but a simple image processing library. First is an ability to represent a variety of image types, typically the discriminate feature being the pixel type, e.g. binary, short integer, long integer, or floating point. The second issue is implementation of image processing algorithms that will be able to operate on each of the supported image representations. In many traditional library designs this leads to reimplementation of the same algorithm many times, once for each possible image representation. Some attempts to alleviate this problem introduce elaborate schemes of dynamic pixel representation and registration. This results in single algorithm implementation, however, due to dynamic pixel registration, efficiency of these implementations is poor. In this paper, we investigate use of parameterized algorithms and design issues involved in implementing them in C++. We permit single expression of the algorithm to be used with any concrete representation of an image. Use of advanced features of C++ and object-oriented programming allow us to use static pixel representations, where pixel types are resolved during compile time instead of run time. This approach leads to very flexible and efficient implementations. We have both advantages: single algorithm implementation for numerous image representations, and best possible speed of execution.

Challenges of adapting a dual-wavelength infrared imaging system as an industrial inspection tool

Non-contact thermal measurement techniques such as on-line thermography can be valuable tools for process monitoring and quality control. Many manufacturing processes such as welding or casting are thermally driven, or exhibit strong correlation between thermal conditions and product characteristics. Infrared inspection of self-emitted radiation can provide valuable insight into process parameters not routinely observed yet which dominate product quality. Recent advances in IR system technology coupled with significant reductions in cost are making thermography a viable tool for such on-line monitoring. This paper describes the implementation of a novel rugged thermal imaging system based on a dual-wavelength technique for a large intelligent process monitoring project. The object of the portion described herein is to deploy a non- contact means of monitoring tooling surface thermal conditions. The technical and practical challenges of developing such a non-contact thermal measurement system for continuous inspection in an industrial environment are discussed, and methods of resolving them are presented. These challenges include implementation of a wavelength filter system for quantitative determination of the surface temperature. Also, unlike visible-spectrum machine vision applications, surface emissivity of the test object as well as reflections from other IR emitters must be taken into account when measuring infrared radiation for a part or process. However, the primary issues that must be addressed prior to deployment are compensation for ambient temperature conditions and optimization of the calibration process. Other issues center on remote camera control, image acquisition, data synchronization, and data interpretation. An example application of this system, along with preliminary data, is described.

Color AC plasma panel barrier measurement system

A system for measuring barriers in a color AC plasma panel has been developed. Barriers are used in this type of display to prevent phosphors in cells adjacent to lit cells from being excited which adversely affects color purity. The geometry of the barriers is a significant factor for successful operation of color plasma panels and must be measured to verify that the barriers are within specifications. Barrier height is on the order of several mils with a pitch on the order of about 10 mils. A system developed for spacer measurements was available for this application. However, it did not have sufficient light sensitivity because the barriers reflect light much less efficiently than traditional panels. The original system employed a light section microscope for height measurement. The video amplifier gain was boosted significantly in the frame grabber and frame integration was provided to reduce noise. Finally, background subtraction was provided to remove shading variations associated with the normally insignificant dark current of the CCD sensor. Once a good image had been obtained, morphological processing was performed to reduce noise and centroid calculations were performed to provide an accurate measure of the barrier surface height.