Topic
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.
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20 Aug 2006
TL;DR: This method is unique in not restricting the camera position, thus allowing greater flexibility than scanner-based or fixed-camera-based approaches and can produce a very sharp, high resolution and accurate full page mosaic from small image patches of a document.
Abstract: In this paper we present an image mosaicing method for camera-captured documents. Our method is unique in not restricting the camera position, thus allowing greater flexibility than scanner-based or fixed-camera-based approaches. To accommodate for the perspective distortions introduced by varying poses, we implement a two-step image registration process that relies on accurately computing the projectivity between any two document images with an overlapping area as small as 10%. In the overlapping area, we apply a sharpness based selection process to obtain seamless blending across the border and within. Experiments show that our approach can produce a very sharp, high resolution and accurate full page mosaic from small image patches of a document.
52 citations
Proceedings Article•
01 Aug 2008TL;DR: This article presents a synthetic image set for validation of cell image analysis algorithms, and proposes to use the simulated images for benchmarking along with manually labeled images, and presents case studies of tuning and testing a cell imageAnalysis algorithm based on simulated images.
Abstract: This article presents a synthetic image set for validation of cell image analysis algorithms. To address the problem of validation, we have previously developed a simulation framework for cell population images. Here, we apply the simulation for generating a benchmark set of cell images with varying characteristics. The value of simulation is in the ground truth information known for the generated images. Traditionally, the ground-truth has been obtained through tedious and error-prone manual segmentation of the images. While such approach cannot be fully replaced, we propose to use the simulated images for benchmarking along with manually labeled images, and present case studies of tuning and testing a cell image analysis algorithm based on simulated images.
52 citations
01 Sep 2013
TL;DR: A new set of high quality color image sequences captured with the authors' professional digital cinema camera and the set is freely available for FTP at ftp://imageset@ftp.arri.de/
Abstract: In 1991 Kodak released a set of 24 digital color images derived from a variety of film source materials. Since then, most image processing algorithms have been developed, optimized, tested and compared using this set. Until a few years ago it was considered “the” image set; however, today it shows its limitations. Researches have expressed their need for better, more up-to-date material. We present a new set of high quality color image sequences captured with our professional digital cinema camera. This camera stores uncompressed raw sensor data and the set is freely available for FTP at ftp://imageset@ftp.arri.de/ password: imageset.
52 citations
TL;DR: The Centroid method is presented, which extracts and uses similarity patterns that consistently appear across all images to reduce set redundancy and achieve higher lossless compression in sets of similar images.
52 citations
TL;DR: The nearest-farthest subspace (NFS) classifier is proposed which exploits the both relationships to classify a test image and the comparisons with NS classifier and other state-of-the-art methods on four famous public face databases demonstrate the good performance of FS and NFS.
52 citations