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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21 Jun 1996
TL;DR: An algorithm is presented that generates cores of 3D medical images and also generalizes to finding implicitly defined manifolds of codimension greater than one using the geometric definition of height ridges and mathematical models of manifold intersections.
Abstract: The authors present an algorithm, called marching cores, that generates cores of 3D medical images and also generalizes to finding implicitly defined manifolds of codimension greater than one. As one marches along the core, one use medialness kernels to generate new medialness values and then find ridges in the extended medial space using the geometric definition of height ridges and mathematical models of manifold intersections. Results from both a test image and a CT image illustrate the algorithm.
32 citations
01 Jan 2012
TL;DR: A completely new approach to the colour constancy problem by unsupervised learning of an appropriate model for each training surface in training images, which has the advantage of overcoming multi-illuminant situations, which is not possible for most current methods.
Abstract: Exemplar-based learning or, equally, nearest neighbour methods have recently gained interest from researchers in a variety of computer science domains because of the prevalence of large amounts of accessible data and storage capacity. In computer vision, these types of technique have been successful in several problems such as scene recognition, shape matching, image parsing, character recognition and object detection. Applying the concept of exemplar-based learning to the problem of colour constancy seems odd at first glance since, in the first place, similar nearest neighbour images are not usually affected by precisely similar illuminants and, in the second place, gathering a dataset consisting of all possible real-world images, including indoor and outdoor scenes and for all possible illuminant colours and intensities, is indeed impossible. In this paper we instead focus on surfaces in the image and address the colour constancy problem by unsupervised learning of an appropriate model for each training surface in training images. We find nearest neighbour models for each surface in a test image and estimate its illumination based on comparing the statistics of pixels belonging to nearest neighbour surfaces and the target surface. The final illumination estimation results from combining these estimated illuminants over surfaces to generate a unique estimate. The proposed method has the advantage of overcoming multi-illuminant situations, which is not possible for most current methods. The concept proposed here is a completely new approach to the colour constancy problem. We show that it performs very well, for standard datasets, compared to current colour constancy algorithms.
32 citations
Patent•
12 Jul 2004
TL;DR: In this paper, the image reconstruction of the CT image is executed from the X-ray projection data scanned by a gantry 100 using an FBP (filter back projection) method and the image quality of a prescribed comparison image is improved by a method for successive approximation.
Abstract: PROBLEM TO BE SOLVED: To provide an image processing apparatus which can smoothly correct the other portion while maintaining the sharpness of the edge portion of a specific region of a CT image and can quantitatively evaluate a reconstructed image, an image processing method and an X-ray CT system. SOLUTION: The image reconstruction of the CT image is executed from the X-ray projection data scanned by a gantry 100 using an FBP (filter back projection) method and the image quality of a prescribed comparison image is improved by a method for successive approximation. Then, a prescribed ROI is set on the updated comparison image to calculate standard deviation. Here, whether or not the image quality improvement of the comparison image is further necessary is determined and when it is determined to be necessary, the image quality of the above comparison image is further improved by the method for successive approximation. On the other hand, when the image quality improvement is determined to be unnecessary, the above comparison image is outputted as the CT image. COPYRIGHT: (C)2006,JPO&NCIPI
31 citations
Patent•
05 Jul 2005TL;DR: In this paper, face image of a character in an image represented by image data fed to a mask data creating apparatus is detected, face image areas of the detected character are respectively extracted by different two types of processing.
Abstract: When a face image of a character in an image represented by image data fed to a mask data creating apparatus is detected, face image areas of the detected character are respectively extracted by different two types of processing. An appropriate degree is calculated for each of the face image areas extracted by the two types of extraction processing. The face area for which the higher relevance factor is calculated is used, to create mask data.
31 citations
Patent•
21 Feb 2003TL;DR: In this article, a pattern matching technique provides a small number of circuits for flexibly performing a pattern match on image data in various two-dimensional matrix formats at a high speed, which also provides a high-speed image area separation and to promote the stability in the image area determination.
Abstract: A pattern matching technique provides a small number of circuits for flexibly performing a pattern match on image data in various two-dimensional matrix formats at a high speed The pattern matching technique also provides a high-speed image area separation and to promote the stability in the image area determination
31 citations