There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

[신간의 별자리x] 우리/미술, 그리고 ‘슬픔의 박물관’

Data Mining Practical Machine Learning Tools and Techniques

MUCKE aims to mine a large volume of images, to structure them conceptually and to use this conceptual structuring in order to improve large-scale image retrieval. The last decade witnessed important progress concerning low-level image representations. However, there are a number problems which need to be solved in order to unleash the full potential of image mining in applications. The central problem with low-level representations is the mismatch between them and the human interpretation of image content. This problem can be instantiated, for instance, by the incapability of existing descriptors to capture spatial relationships between the concepts represented or by their incapability to convey an explanation of why two images are similar in a content-based image retrieval framework. We start by assessing existing local descriptors for image classification and by proposing to use co-occurrence matrices to better capture spatial relationships in images. The main focus in MUCKE is on cleaning large scale Web image corpora and on proposing image representations which are closer to the human interpretation of images. Consequently, we introduce methods which tackle these two problems and compare results to state of the art methods. Note: some aspects of this deliverable are withheld at this time as they are pending review. Please contact the authors for a preview.

http://ieeexplore.ieee.org/iel2/4524/12820/00592460.pdf

Image Processing

Edge Detection Using MultiRing on Spiral Architecture.

Human key posture extraction will benefit for human action recognition, human action retrieval, human behaviour understanding and so on. This paper proposes an approach to select key postures from a human action video based on Radon transform. Cluster is used on the Radon transform to select the final key postures of human action video. The approach does not require motion extraction from the human action video. The experiments results show that the proposed approach is efficient.

Extracting key postures using radon transform

The invention provides a compound of formula I (I) wherein R represents hydrogen, lower alkyl, phenyl, halophenyl, loweralkylphenyl, loweralkoxyphenyl or aralkyl of 7 to 12 carbon atoms, R1 represents hydrogen or fluorine, R2 represents hydrogen, fluorine, chlorine or trifluoromethyl, n is 1 or 2 or pharmaceutically acceptable acid addition salt thereof. Pharmaceutical compositions containing the compounds are also covered as are methods of treating ulcers or hypersecretion using the compounds. Corresponding thiocompounds, useful as intermediates, are also disclosed.

/pdf/a-robust-hough-transform-based-method-for-direction-3i0xxsetrj.pdf

A Robust Hough Transform Based Method for Direction Detection and Its Application.

Developing a spatial searching tool to enhance the search capabilities of large spatial repositories for Geographical Information System (GIS) update has attracted more and more attention. Typically, objects to be detected are represented by many local features or local parts. Testing images are processed by extracting local features which are then matched with the object's model image. Most existing work that uses local features assumes that each of the local features is independent to each other. However, in many cases, this is not true. In this paper, a method of applying the local cooccurring patterns to disclose the cooccurring relationships between local features for object detection is presented. Features including colour features and edge-based shape features of the interested object are collected. To reveal the cooccurring patterns among multiple local features, a colour cooccurrence histogram is constructed and used to search objects of interest from target images. The method is demonstrated in detecting swimming pools from aerial images. Our experimental results show the feasibility of using this method for effectively reducing the labour work in finding man-made objects of interest from aerial images.

/pdf/applying-local-cooccurring-patterns-for-object-detection-10q2v2g5cx.pdf

Applying local cooccurring patterns for object detection from aerial images

Edge detection plays an important role in image processing area This paper presents a Canny edge detection method based on bilateral filtering which achieves better performance than single Gaussian filtering In this form of filtering, both spatial closeness and intensity similarity of pixels are considered in order to preserve important visual cues provided by edges and reduce the sharpness of transitions in intensity values as well In addition, the edge detection method proposed in this paper is achieved on sampled images represented on a real hexagonal structure Due to the compact and circular nature of the hexagonal lattice, a better quality edge map is obtained on the hexagonal structure than common edge detection on square structure Experimental results using proposed methods exhibit also the faster speed of detection on hexagonal structure

Xiangjian He

Papers

Edge Detection Using MultiRing on Spiral Architecture.

Extracting key postures using radon transform

A Robust Hough Transform Based Method for Direction Detection and Its Application.

Applying local cooccurring patterns for object detection from aerial images

Canny Edge Detection Using Bilateral Filter on Real Hexagonal Structure