Standard test image

About: Standard test image is a research topic. Over the lifetime, 5217 publications have been published within this topic receiving 98486 citations.

Independent component analysis for texture defect detection

Abstract: In this paper, a novel method for texture defect detection is presented The method makes use of Independent Component Analysis (ICA) for feature extraction from the nonoverlapping subwindows of texture images and classifies a subwindow as defective or nondefective according to Euclidean distance between the feature obtained from average value of the features of a defect free sample and the feature obtained from one subwindow of a test image The experimental results demonstrating the use of this method for visual inspection of textile products obtained from a real factory environment are also presented

Novel automatic PCB inspection technique based on connectivity

Abstract: This paper presents a novel technique for PCB inspection based on the comparison of the Connected Table of a Reference and a Test Image. The method is based on connected component analysis, which is a natural way to extract the connectivity information of the conductors of a PCB. The registration of the PCB holes, which is a common problem related to referential model techniques, is solved by the concept of zone of influence of each hole. This paper describes the method and its implementation using standard Morphology Image Processing techniques. A result of applying the technique to real images is shown.

Universal Face Photo-Sketch Style Transfer via Multiview Domain Translation

Abstract: Face photo-sketch style transfer aims to convert a representation of a face from the photo (or sketch) domain to the sketch (respectively, photo) domain while preserving the character of the subject. It has wide-ranging applications in law enforcement, forensic investigation and digital entertainment. However, conventional face photo-sketch synthesis methods usually require training images from both the source domain and the target domain, and are limited in that they cannot be applied to universal conditions where collecting training images in the source domain that match the style of the test image is unpractical. This problem entails two major challenges: 1) designing an effective and robust domain translation model for the universal situation in which images of the source domain needed for training are unavailable, and 2) preserving the facial character while performing a transfer to the style of an entire image collection in the target domain. To this end, we present a novel universal face photo-sketch style transfer method that does not need any image from the source domain for training. The regression relationship between an input test image and the entire training image collection in the target domain is inferred via a deep domain translation framework, in which a domain-wise adaption term and a local consistency adaption term are developed. To improve the robustness of the style transfer process, we propose a multiview domain translation method that flexibly leverages a convolutional neural network representation with hand-crafted features in an optimal way. Qualitative and quantitative comparisons are provided for universal unconstrained conditions of unavailable training images from the source domain, demonstrating the effectiveness and superiority of our method for universal face photo-sketch style transfer.

Protective device for safeguarding a hazardous area and method of checking the functional reliability of such a device

Abstract: The present invention discloses a protective device for safeguarding a hazardous area and a method for checking the functional reliability of such a device. The protective device has an image recording unit with an image sensor which includes a large number of light-sensitive pixels. During operation, the image recording unit records an object image. The image sensor is also supplied with a defined test image in order to check the functional reliability, wherein the test image recorded by the image sensor is compared with a defined expectation. According to one aspect of the invention, the object image is specifically made dynamic by means of a testing device and the modified object image is used as the test image.

Authenticity and integrity of digital mammographic images

Abstract: Image authenticity and integrity is an important issue in a telemammography system. We present an algorithm which can embed encrypted image and patient information into an image. The embedded information can be extracted and decrypted by the receiving site to verify the patient identification and confirm image authenticity and integrity. Because of the large size of mammographic images comparing to other images, data embedding in a mammogram is relatively easier to be implemented. By analyzing the noise gray level of our digital mammography system, we know that the least-significant bits of the image are noise caused by the imaging device. So these bits can be used for data embedding. The methods include: (I) Calculate the check-sum of the image and extract patient information from DICOM header, (2) Encrypt the check-sum and patient information using public-key encryption strategy, (3) Generate a set of uniformly distributed pseudo-random numbers and put the encrypted check-sum and patient information into randomly selected pixel locations. Three mammographic images are selected for our experiment. Two images are the digitized mammogram with a large breast and a small breast, and the other is the direct digital mammogram. About 500 characters of patient information and a 32 bits check-sum are embedded into each image. By comparing the original image and the embedded image from a 2k x 2k monitor, we found three embedded images of large size and small size of digitized mammogram as well as direct digital mammogram have no quality degradation. To prove the effectiveness of this method, we change the value of one pixel which is selected randomly in the embedded image. Then, we use our extraction algorithm to detect the integrity of this image. The results show we can not only extract the embedded patient information correctly, but also detect the slight difference between the original image and the altered image. Our preliminary results demonstrate that embedding extra information into an image using data hiding technology is an effective method for image integrity in telemammography.