Hexin Chen

A Dynamic Blood Information Management System Based on RFID

As a patient and recipient of a blood transfusion, it is important for him or her to receive the safest blood possible. Information about the donated blood should be under the track to guarantee the quality of the blood source. In this paper, we present a RFID-based blood information management system that aims at ensuring the quality of the blood and increasing the efficiency of operation management. In this system, the fingerprint sensor is adopted to enable the process of identifying blood donor more reliable and credible and RFID tag is used to make the management more convenient. In addition, GPRS is applied in this system so that real-time data can be transmitted between the bloodmobile and blood center through wireless Internet

Unsupervised image change detection means based on improved 2-D entropy

Change detection in images of a given scene acquired at different times is one of the most interesting topics of remote image processing, which finds important applications within different contexts. Most methods are based on difference image in existing literatures, whose key is how to automatically detect change area of the difference image. In this paper, a novel image change detection means based on 2-D histogram formed by pixel gray levels and the local average gray levels is proposed. First, the 2-D histogram is segmented by a line passing through the diagonal of 2-D histogram in a certain direction. Second, the improved 2-D entropy is defined to acquire the optimal segmentation direction and the optimal threshold by searching 2D maximal entropy. And the 2-D histogram is segmented into unchanged region and change region. Then the change area in different image is detected based on the change region of 2-D histogram. Finally, the change detection means proposed in the paper is compared to traditional means by carrying out an experiment on a synthetic data set artificially generated. Theoretical analysis and experiment result show that this algorithm is more accurate on detection precision and faster on detection speed.

Multi-dimension Multimedia Retrieval Model Implementation Based on XML Database

Derived from the thought of data warehouse, data cube and xml, this paper presents a new database structure model which organizes the multimedia data in a multi-dimensional data cube based on XML Database. In this data cube of XML, clustered data are stored in instance table. A leading data corresponding are stored in dimension table. The relational model is helpful to construct data model, but it lacks flexibility, now the new data model can complement the defect of relational model. When querying, a leading data is gained from dimension table of XML¿then receiving the multimedia data through XQuery.

Multimedia database retrieval based on data cube

Derived from the thought of data warehouse and data cube, this paper presents a new database structure model which organizes the multimedia data in a multi-dimensional data cube. Clustered data are stored in instance table in the data cube. A corresponding leading data are stored in dimension table. When querying, a leading data is gained from dimension table firstly, followed by a k-nearest neighbor query from the corresponding category, the retrieval results are returned. Because of not in need of searching all the records in database, the time cost is low.

Audio-video synchronous coding based on mode selection in H.264

An embedded audio-video synchronous coding scheme based on mode selection is proposed in the paper. In H.264, many mode types are employed to conduct inter prediction for determining the best one to achieve good coding efficiency. In the paper, the audio information is embedded into video stream by modulating the best mode in inter prediction, and then synchronous coding is applied to the mixing video and audio. The modulation is based on the cost function and mapping rules between the mode types and the audio bits. We have verified the proposed scheme based on H.264/AVC using JM 11.0 and evaluated it by four objective indicators: the video quality, the embedded cost, the change of bit-rate and the change of total encoding time. The experimental results show that this scheme has achieved synchronous coding between audio and video with small influence on the above four objective indicators.

Research on CAVLC audio-video synchronization coding approach based on H.264

In order to solve the problem of synchronization of audio and video effectively, a new method based on the H.264/AVC encoder is proposed. The new approach applies the highest-frequency sign bit of the Trailing Ones, which is in Context Adaptive Variable Length Coding (CAVLC) during the entropy coding process, to embed audio information into video stream. Experimental results show that the proposed method achieves synchronization between audio and video at no bit-rate increase, and the original audio information can be extracted from the H.264/AVC decoder without any distortion. At the same time, it has little effect on the quality of video.

Video Compression Based on Adaptive Multidimensional Vector Matrix DCT

The traditional multi-dimensional vector matrix discrete cosine transform compression adopts video frame segmentation of fixed block size. In fact, the texture complexities of image in different regions are usually very different, so transformation adaptively with proper block size, not only further improves the compression performance, but also gets better improvement in subject evaluation. A three-dimensional variable block size video images segmentation method is proposed by using gradient edge detection operator as image activity criterion, and implement variable block size multi-dimensional vector matrix transform coding, experimental results show that the proposed method gets better performance than H. 264, and the quality of the reconstructed images is improved in subject evaluation. It is very efficient for low Bit Rate video compression.

Color image transform coding based on three dimensional variable vector matrix size segmentation

Three-dimensional vector matrix discrete cosine transform coding (3DVMDCT) deals with each component of color image in a unified model, fully eliminates the correlation between them and gets an obvious advantage. But its block-size of image segmentation is fixed and does not fully take into account that there are different statistical properties in different regions. In this paper, we take gradient as the image measure activity (IAM), propose a new method—variable matrix-size three-dimensional vector matrix image segmentation (VMS-3DVMDCT), and implement the corresponding multi-dimensional vector matrix discrete cosine transform coding, experimental results show that, compared with the fixed block partition, the proposed algorithm improves PSNR at most 1dB, and the quality of the reconstructed image is improved in subject evaluation, much better than JPEG.

Management System for Multi-Dimension Multimedia Data Based on Matrix Division Method and Star Structure

Derived from the thought of data cube, this paper presents a new database structure model which organizes multimedia data in a multi-dimensional data cube and presents a new theory for storing non-structure data named matrix division method. With the new theory to organize and store multimedia data, clustered data are stored in instance table. A leading data corresponding are stored in dimension table. The relational model is suitable for fixed structured data. However video data is non-structure data. For the purpose of efficient constructing, storing and retrieving video data, we give and implement the new data model to complement the defect of relational model.

Highlight detection for video content analysis through double filters

Highlight detection is a form of video summarization techniques aiming at including the most expressive or attracting parts in the video. Most video highlights selection research work has been performed on sports video, detecting certain objects or events such as goals in soccer video, touch down in football and others. In this paper, we present a highlight detection method for film video. Highlight section in a film video is not like that in sports video that usually has certain objects or events. The methods to determine a highlight part in a film video can exhibit as three aspects: (a) locating obvious audio event, (b) detecting expressive visual content around the obvious audio location, (c) selecting the preferred portion of the extracted audio-visual highlight segments. We define a double filters model to detect the potential highlights in video. First obvious audio location is determined through filtering the obvious audio features, and then we perform the potential visual salience detection around the potential audio highlight location. Finally the production from the audio-visual double filters is compared with a preference threshold to determine the final highlights. The user study results indicate that the double filters detection approach is an effective method for highlight detection for video content analysis.