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.

Process and device for image display with automatic defect correction by feedback

Abstract: An automatic defect correction drive utilizing feedback in an image display device. According to the present invention, during an acquisition phase, a test image constituted of bright points of known positions distributed on a screen is displayed. This displayed image is then analyzed via an image acquisition device, to deduce from it the scanning, focusing and amplitude corrections to be applied to the display, so that the test pixels displayed on the screen have their expected positions and characteristics. These corrections are then interpolated for the intermediate pixels between test points, and then, during a continuation phase, these corrections are updated.

Using linking features in learning non-parametric part models

Abstract: We present an approach to the detection of parts of highly deformable objects, such as the human body. Instead of using kinematic constraints on relative angles used by most existing approaches for modeling part-to-part relations, we learn and use special observed 'linking' features that support particular pairwise part configurations. In addition to modeling the appearance of individual parts, the current approach adds modeling of the appearance of part-linking, which is shown to provide useful information. For example, configurations of the lower and upper arms are supported by observing corresponding appearances of the elbow or other relevant features. The proposed model combines the support from all the linking features observed in a test image to infer the most likely joint configuration of all the parts of interest. The approach is trained using images with annotated parts, but no a-priori known part connections or connection parameters are assumed, and the linking features are discovered automatically during training. We evaluate the performance of the proposed approach on two challenging human body parts detection datasets, and obtain performance comparable, and in some cases superior, to the state-of-the-art. In addition, the approach generality is shown by applying it without modification to part detection on datasets of animal parts and of facial fiducial points.

Cattle face recognition using local binary pattern descriptor

Abstract: In response to the current need for positive identification of cattle traceability, this paper presents a novel facial representation model of cattle based on local binary pattern (LBP) texture features and some extended LBP descriptors are also introduced. Algorithm training was performed independently on several normalized gray face images of 30 cattle (with each having a set of six, seven, eight, and nine images respectively). Robust alignment by sparse and low-rank decomposition was also used to align the images because of variations in illumination, image misalignment and occlusion in the test image. The performance of this technique was assessed on a separate set of images using the weighted Chi square distance [1]. The LBP descriptor shows its excellence in efficiency and accuracy with regard to the encouraging results on cattle face recognition. More training sets and modified algorithms will be considered to improve recognition rates. Future work should aim at improving the automation of the system and combining the LBP histogram with other effective histograms.

Assessment of satellite image segmentation in RGB and HSV color space using image quality measures

Abstract: This paper presents a comparative study of the segmentation of satellite images in RGB and HSV color space using modified fuzzy c means clustering algorithm. The segmented images are compared with the original input images by using number of bivariate image quality parameters. These parameters measure the similarity between the input and the segmented image on the basis of comparing the corresponding pixels of the two images and present a numerical value as a result. The experiments are performed on GeoEye-1 satellite images to test the efficiency and robustness of the proposed method

Digital process and apparatus for convergence correction having adjustment points and correction portions determined by the adjustment point selected

Abstract: A plurality of images superimposed to form a composite image on the screen of a television monitor are brought into convergence (register) by forming a reference image on the screen, the reference image including a plurality of reference points, and superimposing a test image on the reference image. The test image is similar to the reference image and includes a plurality of adjustment points respectively corresponding to the reference points. The test image further includes at least one correction portion corresponding to a given portion of the reference image, the correction portion including a given subset of the adjustment points. An adjustment point is selected within such subset, the position of the selected adjustment point is adjusted with respect to the reference point corresponding thereto, and the positions of the other points within the correction portion are simultaneously and proportionally adjusted, thereby establishing a substantial convergence of the correction portion with respect to the given portion of the reference image. The process is repeated for other corresponding image portions as necessary to establish substantial convergence of all corresponding portions of the two images. In the same manner convergence of a third image with the first two is established.