Component Testing for VsImaging Library Using Pixel Comparison Technique (original) (raw)
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Institute of Engineers, Chandigarh, INDIA, 2021
Test automation is one of the essential aspects of verification and validation of embedded software. Test automation plays a crucial role to meet the deadlines to launch a product. In terms of embedded software, display (graphical) validation is a bit complex to automate compared totext or numeric testing where references are available for making comparisons. In the work presented, we addressed the problem of comparing digital images to find the similarity which can facilitate the embedded software test automation. Embedded testing automation is widely used to reduce development time and cost. However, still, we are not able to achieve 100% test automation due to dependency on a few manual observation aspects like the display output. Most of the embedded products have output displays thatproduce text, symbols or images and their testing is conducted manually. The manual observation involved can be automated with thepresented work to reduce significant testing time and reduce paradox errors.
Automated Random Testing of Image Processing Applications with Effectiveness Measure
Jameel, Tahir, Meng Xiang Lin, and Saqib Yousaf. "Automated Random Testing of Image Processing Applications with Effectiveness Measure." Applied Mechanics and Materials. Vol. 555. 2014.
Automating software testing process has remarkably reduced the cost of manual efforts and made testing considerably fast. Recently, image processing has been extensively used in different software applications and their significance implies a well-tested reliable system. Testing of these applications require semantically complex multidimensional image data. Whereas, the image databases are extremely large in size and testing of application on each image is not possible in constrained time. In order to meet these challenges, an automated testing tool is required which is capable of reporting bugs using a finite number of input images and can quantify its effectiveness on the basis of a coverage metric. In this paper, we present a tool IMTEST based on a novel technique to test image processing applications that aims to achieve high program coverage and capable to report bugs that manifest during testing process. It selects images randomly from an image database and gives input to the instrumented version of the code under test. The instrumented code replica is generated by our tool, inserting additional analysis code apart from original code. This allows us to measure the coverage achieved during program execution for a particular input image. A coverage vector is designed to record program coverage during iterative execution of instrumented program under test for different input images. Any unexpected program behavior is recorded as bug that manifests during testing process. A stopping criteria is used to conclude the testing in a considerable time duration. The tool is tested on real applications and the result shows that IMTEST reported real bugs which are reproducible with the specified images and is useful to improve software quality.
Image Processing Algorithms for Non-destructive Testing
Journal of the Korea Society of Computer and Information, 2016
In this study, an image processing algorithm was developed to increase readability of the images of specific parts of a KTX train acquired by using a mobile digital radiographic testing device in a situation where a running train is stopped. The image processing algorithm was realized by using a Visual C++ development tool.
GLSCENEINT: A Synthetic image generation tool for testing computer vision systems
This paper presents a synthetic image generation tool that is useful for testing computer vision algorithms. The application interprets scene description files written in a language we developed. Image rendering is done using OpenGL, as opposed to the more usual ray-tracing techniques, in order to gain speed. An arbitrary sub-pixel accuracy can be used. The synthetic image generation application is useful for testing calibration methods, edge extraction stereo reconstruction methods, lane detectors, grouping etc.
Image comparison Methods & Tools: A Review
Future of Smart technologies lies in its ability to collect the field data in an affordable methods & tools. Due to popularity of smart phones and CCTV cameras, a significant amount of data can be collected in image format. The ability to process the image data helps in developing solutions that can solve industrial problems. There are numerous methods for image comparison and processing. Current papers aim at reviewing the available tools & techniques for Image processing & comparison. These tools in connection with big data plat form can create a user-friendly solution in solving the industrial problem. Keywords—Image Comparison, Tools, Methods.
Test Image Generation using Segmental Symbolic Evaluation
International Journal of Networked and Distributed Computing, 2014
Image processing applications have played a vital role in modern life and they are required to be well tested due to their significance and human dependence on them. Testing of image processing application is difficult due to complex nature of images in terms of their generation and evaluation. The presented technique is first of its type to generate test images based on symbolic evaluation of program under test. The idea is based on the fact that, neighboring image operations are applied by selecting a segment of image pixels called a window, and iterated by sliding window over entire image. We imitate neighboring operations using symbolic values for the pixels rather than concrete values. The path constraint is extracted for each path in the program under test and solved for concrete solutions. Test images are generated based on solution of path constraints for each identified path. We have tested the proposed scheme on different programs and the results show that test images are successfully generated for each path to ensure the path coverage of the program under test and identifying infeasible paths.
TESTIMAGES: a large-scale archive for testing visual devices and basic image processing algorithms
We present the TESTIMAGES archive, a huge and free collection of sample images designed for analysis and quality assessment of different kinds of displays (i.e. monitors, televisions and digital cinema projectors) and image processing tecnhiques. The archive includes more than 2 million images originally acquired and divided in four different categories: SAMPLING and SAMPLING_PATTERNS (aimed at testing resampling algorithms), COLOR (aimed at testing color rendering on different displays) and PATTERNS (aimed at testing the rendering of standard geometrical patterns). The archive is currently online as a SourceForge project and, even if not yet publicized in the scientific community, it has already been used in different contexts and cited in scientific publications. We plan to extend the archive including datasets for other kinds of specific analyses.
Autonomous Method for Object Based GUI Testing using Image Processing
One of the most important and crucial steps of the software development lifecycle is testing the graphical aspects of the application's user interface. The major challenge here is to accurately detect and test the various visual elements of the application, in order to ensure its complete functionality. The proposed method uses image processing techniques to autonomously detect objects within the GUI application, based on the shape of the object. In the process of arriving at an optimized solution, a popular blob detection algorithm (MSER) has been studied and analyzed. One of the drawbacks of this method is its high levels of sensitivity thus resulting in its poor accuracy and making it unsuitable for such an application. Keeping this in mind, an alternate object identification and localization technique has been put forward. Comparisons done after thorough experimentation indicates this method to be more accurate in terms of detecting various objects present within the GUI application, thus aiding the testing process by making it completely autonomous and fail-proof.
Automated test system for JPEG video encoder-decoder card pairs
Computing & Control Engineering …, 1998
The quality of video processing equipment is related to the quality of the images it produces. Some algorithms which can objectively assess the quality of images produced by image processing equipment with respect to a set of reference images are described. These algorithms are used in an automatic test system developed to functionally test JPEG encoder-decoder card pairs.
SSIM Technique for Comparison of Images
International Journal of Innovative Research in Science, Engineering and Technology, 2014
Now days there are different methods are present for evaluation of features of images, but there is no common effort developed for the comparison of the quality of image. We, in this paper are interested in quality evaluation of images so we are capturing the images from different cameras. The cameras we are using are of different configurations, specification and companies. The first work here is to capture the same scene with different cameras. While capturing the image, image can be affect by different types of distortion which we are discussing in this paper. The next step is to extract the special features of images. There are several features on the basis of which we can compare the quality of images. These features are contrast, luminance, edge base structure index, structural similarity(SSIM) etc. For advancement as we are extracting features of image and for quality improvement we are processing image with techniques for better result. Hence we can get the best quality imag...