This paper proposes a fast and robust algorithm for classification and recognition of ships based on the Principal Component Analysis (PCA) method. The three-dimensional ship models are achieved by modeling software o...
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This paper proposes a fast and robust algorithm for classification and recognition of ships based on the Principal Component Analysis (PCA) method. The three-dimensional ship models are achieved by modeling software of MultiGen, and then they are projected by Vega simulating software for two-dimensional ship silhouettes. The PCA method as against the Back-Propagation (BP) neural network method for simulated ship recognition using training and testing experiments, we can see that there is a sharp contrast between them. Some recognition results from simulated data are presented, the correct recognition rate of PCA method improved rapidly for each of the five ship types than that of neural network method, the number of times a ship type is recognized as one of the other ships is reduced greatly.
The framework of a second order morphology algorithm is proposed to enhance the dim small infrared target in sea clutter background with strong detector noise. First, a morphological filters bank is given. Each filter...
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In this paper, we propose a robust visual tracking algorithm based on online learning of a joint sparse dictionary. The joint sparse dictionary consists of positive and negative sub-dictionaries, which model foregroun...
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Simulating and rendering realistic ocean is always one of the most popular and difficult tasks in computer graphics and oceanography. However, because of the restriction of computer software and hardware conditions, m...
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Deblurring camera-based document image is an important task in digital document processing, since it can improve both the accuracy of optical character recognition systems and the visual quality of document images. Tr...
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Vega has been widely used in Virtual Reality (VR) field. Vega infrared (IR) module can implement IR simulation, but Vega IR imaging simulation's general approach does not apply to large-scale scene's infrared ...
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A smart spectral imaging detection method based on the integration of electrically tunable liquid-crystal(LC) Fabry-Perot(FP) microstructure array is proposed. It has very broad application in many fields with advanta...
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Image histogram equalization technology is always a very important basic processing technology in image process field. In infrared image processing system, low contrast and shortage of gray levels often make it very d...
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Passive millimeter-wave (PMMW) imaging offers advantages over visible and IR imaging in having better all weather performance. However the PMMW imaging sensors are state-of-the-art to date, sometimes it is required to...
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Chromosome karyotyping is a critical way to diagnose various hematological malignancies and genetic diseases,of which chromosome detection in raw metaphase cell images is the most critical and challenging *** this wor...
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Chromosome karyotyping is a critical way to diagnose various hematological malignancies and genetic diseases,of which chromosome detection in raw metaphase cell images is the most critical and challenging *** this work,focusing on the joint optimization of chromosome localization and classification,we propose ChromTR to accurately detect and classify 24 classes of chromosomes in raw metaphase cell *** incorporates semantic feature learning and class distribution learning into a unified DETR-based detection ***,we first propose a Semantic Feature Learning Network(SFLN)for semantic feature extraction and chromosome foreground region segmentation with object-wise ***,we construct a Semantic-Aware Transformer(SAT)with two parallel encoders and a Semantic-Aware decoder to integrate global visual and semantic *** provide a prediction with a precise chromosome number and category distribution,a Category Distribution Reasoning Module(CDRM)is built for foreground-background objects and chromosome class distribution *** evaluate ChromTR on 1404 newly collected R-band metaphase images and the public G-band dataset *** proposed ChromTR outperforms all previous chromosome detection methods with an average precision of 92.56%in R-band chromosome detection,surpassing the baseline method by 3.02%.In a clinical test,ChromTR is also confident in tackling normal and numerically abnormal *** extended to the chromosome enumeration task,ChromTR also demonstrates state-of-the-art performances on R-band and G-band two metaphase image *** these superior performances to other methods,our proposed method has been applied to assist clinical karyotype diagnosis.
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