Fabric Pattern Elements Retrieval Based on Cosine Transform

Fabric pattern contains many types of the available pattern elements, which not only can be used for the researchers, but also as the material for the designer. But existing method focus on the complete image retrieval, therefore lack methods of retrieving pattern elements. This article proposes a pattern elements retrieval algorithm based on cosine transform. Firstly, automatically segment the patterns according to size and location and filter the similar primary patterns, then, through cosine transform, analyze elements features in DCT domain, extract amplitude frequency and phase frequency. We employ 2-norm to measure the similarity, search 10 similar pattern elements in the sample library and save them in the design resources library. Experiment results indicate that this algorithm performs well while used in palace costume and carpet patterns, and got more than 75% of the average recall in 100 times experiments

Comparison of two Nd:YAG laser posterior capsulotomy: cruciate pattern vs circular pattern with vitreous strand cutting

AIM： To investigate the effects and safety of neodymium： yttrium-aluminium-garnet（Nd：YAG） laser posterior capsulotomy with vitreous strand cuttingMETHODS： A total of 40 eyes of 37 patients with symptomatic posterior capsular opacity（PCO） were included in this prospective randomized study and were randomly subjected to either cruciate pattern or round pattern Nd：YAG posterior capsulotomy with vitreous strand cutting（modified round pattern）. The best corrected visual acuity（BCVA）, intraocular pressure（IOP）, refractive error, endothelial cell count（ECC）, anterior segment parameters, including anterior chamber depth（ACD） and anterior chamber angle（ACA） were measured before and 1 mo after the laser posterior capsulotomy. RESULTS： In both groups, the BCVA improved significantly（P〈0.001 for the modified round pattern group, P=0.001 for the cruciate pattern group）; the IOP and ECC did not significantly change. The ACD significantly decreased（P〈0.001 for both） and the ACA significantly increased（P=0.001 for the modified round pattern group and P=0.034 for the cruciate group）. The extent of changes in these parameters was not significantly different between the groups.CONCLUSION： Modified round pattern Nd：YAG laser posterior capsulotomy is an effective and safe method for the treatment of PCO. This method significantly changes the ACD and ACA, but the change in refraction is not significant. Modified round pattern Nd：YAG laser posterior capsulotomy can be considered a good alternative procedure in patients with symptomatic PCO.

Tracking a Screen and Detecting Its Rate of Change in 3-D Video Scenes of Multipurpose Halls

An automatic approach is presented to track a wide screen in a multipurpose hall video scene. Once the screen is located, this system also generates the temporal rate of change by using the edge detection based method. Our approach adopts a scene segmentation algorithm that explores visual features （texture） and depth information to perform efficient screen localization. The cropped region which refers to the wide screen undergoes salient visual cues extraction to retrieve the emphasized changes required in rate-of- change computation. In addition to video document indexing and retrieval, this work can improve the machine vision capability in the behavior analysis and pattern recognition.

Host load prediction in cloud based on classification methods

The host load prediction problem in cloud computing has also been received much attention. To solve this problem, we have to use the historical load data to predict the future load level. Accurate prediction methods are useful for host load balance and virtual machine migration. Although cloud is likely to grids at some extent, the length of tasks are much shorter and host loads change more frequently with higher noise. The above characteristics introduce challenges for host load prediction. In this paper, based on the proposed exponentially segmented pattern and the corresponding transformation, prediction problem is transformed into the traditional classification problem, This classification problem can be solved based on the traditional methods, and features are given for training the classification model. For achieving accurate prediction, a new feature periodical coefficient is introduced and some existed classification methods are implemented. Experiments on the real world dataset invalidate the efficiency of the new proposed feature, which is in the most effective combinations of features, it increases successful rate （SR） 1.33%-2.82% and decreases the mean square error （MSE） 1.37%-2.91%. And the results also show that support vector machine （SVM） method can achieve nearly the same performance as the Bayes methods and their performance is about 50% higher in successful rate and 17% better in the mean square error compared to the existed methods.