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.

Developing Matlab scripts for image analysis and quality assessment

Abstract: Image processing is a very helpful tool in many fields of modern sciences that involve digital imaging examination and interpretation. Processed images however, often need to be correlated with the original image, in order to ensure that the resulting image fulfills its purpose. Aside from the visual examination, which is mandatory, image quality indices (such as correlation coefficient, entropy and others) are very useful, when deciding which processed image is the most satisfactory. For this reason, a single program (script) was written in Matlab language, which automatically calculates eight indices by utilizing eight respective functions (independent function scripts). The program was tested in both fused hyperspectral (Hyperion-ALI) and multispectral (ALI, Landsat) imagery and proved to be efficient. Indices were found to be in agreement with visual examination and statistical observations.

Projection-type image display device, image projection method, and computer program

Abstract: There is provided a projection-type image display device including a projection section configured to project an image onto a projection body, a camera section, provided at a position different to an irradiation position of the projection section, configured to image the image projected onto the projection body, a correction amount detection section configured to remove a background from a test image imaged by the camera section at a time when a test pattern is projected onto the projection body from the projection section, detect information of coordinates related to the test pattern within the test image after background removal, and calculate correction parameters for correcting the image projected from the projection section based on the information of the coordinates, and an image correction section which corrects the image projected from the projection section based on the correction parameters.

Phrase-based Image Captioning

Abstract: Generating a novel textual description of an image is an interesting problem that connects computer vision and natural language processing. In this paper, we present a simple model that is able to generate descriptive sentences given a sample image. This model has a strong focus on the syntax of the descriptions. We train a purely bilinear model that learns a metric between an image representation (generated from a previously trained Convolutional Neural Network) and phrases that are used to described them. The system is then able to infer phrases from a given image sample. Based on caption syntax statistics, we propose a simple language model that can produce relevant descriptions for a given test image using the phrases inferred. Our approach, which is considerably simpler than state-of-the-art models, achieves comparable results in two popular datasets for the task: Flickr30k and the recently proposed Microsoft COCO.

Pose Invariant Palmprint Recognition

Abstract: A palmprint based authentication system that can work with a multi-purpose camera in uncontrolled circumstances, such as those mounted on a laptop, mobile device or those for surveillance, can dramatically increase the applicability of such a system. However, the performance of existing techniques for palmprint authentication fall considerably, when the camera is not aligned with the surface of the palm. The problems arise primarily due to variations in appearance introduced due to varying pose, but is compounded by specularity of the skin and blur due to motion and focus. In this paper, we propose a method to deal with variations in pose in unconstrained palmprint imaging. The method can robustly estimate and correct variations in pose, and compute a similarity measure between the corrected test image and a reference image. Experimental results on a set of 100 user's palms captured at varying poses show a reduction in Equal Error Eate from 22.4% to 8.7%.