Wireless Capsule Endoscopy (WCE) generates a large number of images in one examination of a patient. It is very laborious and time-consuming to detect the WCE video, and so limits the wider application of WCE. Color similarity measurement is the key technique of color image segmentation and recognition, as well as the premise of bleeding detection in WCE images. This paper deduces two color vector similarity coefficients to measure the color similarity degree in RGB color space, and based on which, a novel method of intelligent bleeding detection in WCE image is implemented. The novel algorithm is implemented in RGB color space, and is featured with simple computation and practicability. The experiments showed that the bleeding regions in WCE images can be correctly extracted, and the sensitivity and specificity of this algorithm were 90% and 97% respectively.

Proteomic analysis is a powerful technology to enhance our insight into the pathogenesis, biomarkers and prevention of disease. Two-dimensional polyacrylamide gel electrophoresis (2-DE) is an important proteomics tool, where thousands of protein spots can be visualized, resulting in a global view of the state of a proteome. Viral infection will modify the patterns of host cell protein expression, which can affect the normal physiological function of host cell and determine viral pathogenic progress and consequence. To uncover host cellular responses in the early stage of classical swine fever virus infection, a proteomic analysis was conducted using 2DE followed by MALDI-TOF-TOF identification. Altered expression of 21 protein spots in infected pk-15 cells at 24 h p.i. were identified in 2D gels, with 13 of these being characterized by MALDI-TOF-MS/MS. These proteins function in cytoskeletal, energy metabolism, nucleic acid/processing, and cellular stress. The expression alteration of these proteins presents the changes in physiological functions of host cells and provides a clue for further understanding of the mechanisms of CSFV infection and pathogenesis.

To evaluate atherosclerosis, common carotid artery (CCA) lumen segmentation requires outlining the intima contour on transverse view of B-mode ultrasound images. The lumen contours are automatically segmented using a morphology method in this paper. The proposed method is based on self-adaptive histogram equalization, non-linear filtering, Canny edge detector and morphology methods. Experiments demonstrated that the merit (FOM) value of lumen segmentation is 0.705. The comparison between proposed method and manual contours on 180 transverse images of the CCA showed a mean absolute error of 0.47±0.13 mm and mean max distance of 2.08±0.63 mm respectively. These results compare favorably with a clinical need for reducing use variability.

This paper proposes an emotion recognition system using EEG signals, therefore a new approach to emotion state analysis by approximate (ApEn) and wavelet entropy (WE) is described. We have used EEG signals recorded during emotion in five channels (FP1, FP2, T3, T4 and Pz), under pictures induction environment (calm-neutral and negative excited) for participants. After a brief introduction to the concept, the ApEn and WE were extracted from two different EEG time series. The result showed that, the classification accuracy in two emotion states was 73.25% using the support vector machine (SVM) classifier. The simulations showed that the classification accuracy is good and the proposed methods are effective. During an emotion, the EEG is less complex compared to the normal, indicating reduction in active neuronal process in the brain.

A target localization method based on color recogni-tion and connected component analysis is presented in this paper. The raw image is converted to HSI color space through a lookup table and binarized, then followed by a line-by-line scan to find all the connected domains. By setting appropriate threshold for the size of each connected domain, most pseudo targets can be omitted and coordinates of the target could be calculated in the mean time. The main advantage of this method is the absence of extra filtering process, therefore real-time performance of the whole system is greatly improved. Another merit is we introduce the frame difference concept to avoid manually presetting the upper and lower bound for binarization. Thirdly, the localization step is combined with target enumeration, further simplified the implementation.
Experiments on our ARM system demonstrate its capability of tracing multiple targets under a mean frame rate of 15FPS, which satisfied the requirement of real-time video processing on embedded robot systems.

In this paper a multiphase image classification model based on variation level set method is presented. In recent years many classification algorithms based on level set method have been proposed for image classification. However, all of them have defects to some degree, such as parameters estimation and re-initialization of level set functions. To solve this problem, a new model including parameters estimation capability is proposed. Even for noise images the parameters needn’t to be predefined. This model also includes a new term that forces the level set function to be close to a signed distance function. In addition, a boundary alignment term is also included in this model that is used for segmentation of thin structures. Finally the proposed model has been applied to both synthetic and real images with promising results.

Based on the .NET Framework 2.0, the new generation of the windows software development framework .NET Framework 3.0 has four new components, in which the most attractive one is WPF(Windows Presentation Foundation). WPF is a new GUI engine that can provide uniform descriptions and methods for user interface, 2D/3D graphic, document and media. In WPF, the commonly used rotation transformation method for 3D object is RotateTransform3D. This method needs to calculate the state of the camera carefully, otherwise, the 3D object may move anomaly on the screen. To solve this kind of problem, another method is brought forward in the paper, which realizes the rotation transformation by calaulating and changing the attributes (Position, LookDirection, UpDirection) of the camera directly. The method can exhibite the rotation of 3D object distortion-freely, without the anomal movement on the screen. The calculation and the program of the method is simple.