To detect a risk of insurance fraud in a vehicle insurance claim for physical injuries, injury data may be retrieved from previous crashes involving similar type vehicles as the damaged vehicle, and having similar crash characteristics. One or several likelihoods that the claimant suffered physical injuries from the crash may be determined based on the percentage of people who suffered similar types of injuries or similar severity according to the injury data. If the one or several likelihoods are very small, the claim for physical injuries may be flagged as a risk of fraud and a suspicious loss indicator may be transmitted to a mobile computing device for display.

Method and system for comparing automatically determined crash information to historical collision data to detect fraud

This paper provides a review of the automatic methods used for the identification of woven fabrics developed in nearly 30 years starting from the mid-1980s until now. Compared with the manual method based on human eyes and experiences, the objective evaluation technology based on image processing and artificial intelligence holds the advantages of quick response, digital solution and accuracy. This paper describes briefly the background of weave pattern recognition and its development based on an overview of many researches done before. The reported methods can be classified into five categories (diffraction analysis-based, photoelectric analysis-based, frequency domain analysis- based, spatial domain analysis-based, jointed methods and other ones). Both the merits and demerits of frequency domain analysis-based and spatial domain analysis-based methods have been summarized and discussed in this paper. Therefore, it can provide a good reference platform for the researchers to understand and utilize these methods presented for the recognition of woven fabric weave pattern.

A Review of Fabric Identification Based on Image Analysis Technology

Methods, systems, and computer readable media are disclosed for determining a pixel-to-length ratio between a number of pixels disposed over a predetermined length of a reference object within an image of a siding sample and the predetermined length of the reference object. A first and second distance between respective first and second pairs of points within the image corresponding to respective first and second length measurements of the siding sample are determined, as well as a first and second number of pixels disposed between the first and second pair of points, respectively. Furthermore, the method, system, and computer readable medium disclose determining the first length measurement based on the pixel-to-length ratio and the first number of pixels, determining the second length measurement based on the pixel-to-length ratio and the second number of pixels, and identifying a siding product associated with the first and second length measurements.

System and method for automatically measuring the dimensions of and identifying the type of exterior siding

This paper presents an automated and comprehensive system for eliminating rib shadows in chest radiographs, which integrates lung field identification, rib segmentation, rib intensity estimation, and suppression. We designed a region of interest (ROI)-based method to estimate a suitable initial lung boundary for active shape model (ASM) deformation by determining the translation and scaling parameters from the lung ROI. By considering the anatomical structure of the rib cage, we developed a locale sampling scheme to achieve nonparametric rib modeling. This scheme integrates knowledge-based generalized Hough transform (GHT) for accurate rib segmentation. We subsequently estimated rib intensity using the real-coded genetic algorithm (RCGA). Experimental results indicate that the relative conspicuity of the nodules increased after rib suppression, compared to the original image. Additionally, the proposed system uses only one standard chest radiograph, and the dual-energy subtraction technique is not required. Thus, this system is suitable for radiologists and computer-aided diagnosis (CAD) schemes for detecting lung nodules in chest radiographs.

A nonparametric-based rib suppression method for chest radiographs

Automatic recognition of woven fabric structural parameters: a review

This paper proposed a new method based on image processing and pattern recognition technology to recognize the pattern of woven fabric. The method disposed the information of both the top and bottom fabric images. The result of analyzing the regularity of the intensity variation of the horizontal and vertical direction of image can be used to determine the interlacing position of yarn sections. According to encoding the color information of fabric, the types of cross points can be obtained. After getting the color information of fabric on the warp and weft directions, the color pattern could be determined, and it can be used to correct the errors of classification of cross-point classification. Finally a fabric model can be built which contains types of interlacing points and color pattern.

A novel method of intelligent analysis of weave pattern based on image processing technology

Thermally induced stresses play a very important role in controlling the structural reliability of microchip packages. In order to evaluate the magnitude of the warpage of measured objects caused by such stresses, the shadow moire technique was suggested, where how the moire fringes are extracted is the key feature. In this work, an improved filtering algorithm based on a nonlinear diffusion equation is developed and a medial axis transformation and pruning algorithm are applied to extract the skeleton of the moire fringe. In order to remove the forficate fringe and isolated noise fringe, a main fringe extraction algorithm is then used, and this is discussed in detail. According to the moire fringe information extracted from the shadow moire pattern, the three-dimensional image which indicates warpage of the measured object's surface is reconstructed. This demonstrates that the measuring accuracy can be improved up to 2.0 @mm by using a grating of 100 lines per inch.

A method of image preprocessing based on nonlinear diffusion and information extraction

This paper proposed a new method based on secondary encoding technology to recognize the pattern of woven fabric The method disposed the information of both the top and bottom fabric images The result of analyzing the regularity of the intensity variation of the horizontal and vertical direction of image can be used to determine the interlacing position of yarn sections The secondary encoding technology coded the color information of both sides of fabric image, then the types of cross points can be determined After getting the color information of fabric on the warp and weft direction, the color pattern could be obtained, and it can be used to correct the errors of classification of cross-point classification Finally a fabric model can be built which contains types of interlacing points and color pattern

Study on the Intelligent Analysis of Weave Pattern Based on Secondary Encoding Technology

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A novel method of intelligent analysis of weave pattern based on image processing technology

A method of image preprocessing based on nonlinear diffusion and information extraction

Study on the Intelligent Analysis of Weave Pattern Based on Secondary Encoding Technology