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The construction of statistical shape model (SSM) is an important research topic in medical imaging benefited from its robust and nature represent of anatomical structures. Place-march of corresponding landmarks is one of the major factors influencing 3D SSM quality. In this paper, we present a supervised correspondence method for fast building SSM, which includes two main steps, i.e., surface data...
With the development of stone processing and sales, effective stone surface texture image recognition methods are needed. We proposed a new stone surface texture image recognition method based on texture and colour. We combine the following visual features: Gabor features which can well simulate the single cell sensing profile of mammalian visual neurons, The Grey-level Co-occurrence Matrices(GLCM)...
In order to further improve the recognition rate and computing efficiency of modular 2DPCA in face recognition, an improved modular 2DPCA method based on image segmentation is proposed. Firstly, segmentation of threshold value optimization is utilized to segment face image of training samples into several non-overlapping sub-image spaces so that the pixel number has uniform distribution in each sub-image...
Comparing Unmanned Aerial Vehicle (UAV) video image patches is a fundamental task in UAV video image processing. The main difficulty lies in the wide variety of appearance changes in images taken under different UAV imaging conditions, such as jitter, changing points of view, frequent undefined motion, illumination changes and etc. The usual algorithms which are based on the hand-craft features and...
With the development of optical character recognition research, many techniques for printed character recognition have been developed. But the character recognition study for the New Tai Lue has lagged behind. As a result, the digital processes of New Tai Lue have been in troubles. To solve this problem, this paper proposed a printed New Tai Lue character recognition method based on the Back Propagation...
This paper proposes a recognition approach for Semaphore flag signaling (SFS). We use the improved convolutional neural network (CNN) to classify the SFS. In the experiment we made Semaphore flag signaling system (SFSS), which based on CNN. The image can be directly input into the SFSS. Each alphabetic character or control signal is indicated by a particular flag pattern. We shoot the SFS videos by...
Traffic sign detection plays an important role in driving assistance systems and traffic safety. But the existing detection methods are usually limited to a predefined set of traffic signs. Therefore we propose a traffic sign detection algorithm based on deep Convolutional Neural Network (CNN) using Region Proposal Network(RPN) to detect all Chinese traffic sign. Firstly, a Chinese traffic sign dataset...
Speech recognition, as the man-machine interface, plays a very important role in the field of artificial intelligence. Traditional speech recognition methods are shallow learning structure, and have their limitations. This paper uses the Convolution Neural Networks (CNNs) to realize speech recognition. It is an alternative type of neural network that can reduce spectral variation and model spectral...
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