Parabolic Detection Algorithm of Tennis Serve Based on Video Image Analysis Technology

At present, the existing algorithm for detecting the parabola of tennis serves neglects the pre-estimation of the global motion information of tennis balls, which leads to great error and low recognition rate. Therefore, a new algorithm for detecting the parabola of tennis service based on video image analysis is proposed. The global motion information is estimated in advance, and the motion feature of the target is extracted. A tennis appearance model is established by sparse representation, and the data of high-resolution tennis flight appearance model are processed by data fusion technology to track the parabolic trajectory. Based on the analysis of the characteristics of the serve mechanics, according to the nonlinear transformation of the parabolic trajectory state vector, the parabolic trajectory starting point is determined, the parabolic trajectory is obtained, and the detection algorithm of the parabolic service is designed. Experimental results show that compared with the other two algorithms, the algorithm designed in this paper can recognize the trajectory of the parabola at different stages, and the detection accuracy of the parabola is higher in the three-dimensional space of the tennis service.

Research on Sports Video Image Analysis Based on the Fuzzy Clustering Algorithm

Aimed at the shortcomings of the current sports video image segmentation methods, such as rough image segmentation results and high spatial distortion rate, a sports video image segmentation method based on a fuzzy clustering algorithm is proposed. The second-order fuzzy attribute with normal distribution and gravity value is established by using the time-domain difference image, and the membership function of the fuzzy attribute is given; then, the time-domain difference image is fuzzy clustered, and the motion video image segmentation result is obtained by edge detection. Experimental results show that this method has high spatial accuracy, good noise iteration performance, and low spatial distortion rate and can accurately segment complex moving video images and obtain high-definition images. The application of this video image analysis method will help master the rules of sports technology and the characteristics of healthy people’s sports skills through video image analysis and help improve physical education, national fitness level, and competitive sports level.

Determining Relationships between Marbling Scores and Carcass Yield Traits of German Beef Bull Carcasses Using Video-Image Analysis at the 12th and 10th Rib Position of Longissimus Thoracis and EUROP Classification

In contrast to other international beef classification systems, the European EUROP system disregards marbling in meat quality assessment. Instead, it focuses primarily on the assessment of conformation and fat score. Due to the lack of more specific assessment, beef quality in Germany is less known than beef produced in other countries and is largely incomparable to international standards. The aim of this study was to explore the potential of video-image analysis (VIA) for the assessment of bull carcasses for the commercial beef market in Germany. Marbling scores and carcass traits of 170 carcasses were assessed at the 10th/11th and 12th/13th rib-eye sections of longissimus thoracis. Results showed that VIA is able to precisely assess marbling scores at a German cutting position with a close relation (r = 0.83) to the US position. Furthermore, carcass traits integral to the US Yield Grade, such as rib fat (mean 112 mm) and a modified trait of fat/meat ratio, were assessed at the 10th/11th rib-eye position in a process reliably corresponding to the US position (mean 98 mm). EUROP traits showed only weak relationships with marbling scores, VIA measured rib fat thickness, and carcass weights. Although complete validation of video image analysis requires further research with a higher number of test animals, VIA is a viable tool for classifying the variation of German beef carcasses more reliably during the slaughter line and it could valuably supplement EUROP classification traits.