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In order to classify the eaglewood, the work proposed a method of wood fiber segmentation and characteristic extraction based on the eaglewood micrographs. The active contour model was used to extract the contours of the eaglewood micrographs. After screening of wood fiber, the geometric features and shape factors were extracted to form characteristic vectors. After that, SVM was used to achieve the...
This work falls within the framework of the video surveillance research axis. This work falls within the scope of video surveillance. It involves a link between automatic processing and problems related to video surveillance. The job is to analyze video streams coming from a network of surveillance cameras, deployed in an area of interest in order to detect abnormal behavior. Our approach in this...
The most common form of cancer that affects the women is breast cancer. Early detection of breast cancer increases the survival rate. Ultrasound is a common diagnosis tool to detect the abnormalities of the breast. Radiologists observe the features of the mass and classify them into benign and malignant cases. Computer aided diagnosis (CAD) helps the radiologist to identify and analyze the mass more...
In this paper, we propose a new graph-based approach to address the problem of cytological computer-aided diagnostic. Such approach uses our previously introduced formalism of PdEs-based morphology and geometric diffusion on graphs. The approach is illustrated through two applications in cytopathology (involving Feulgen and Papanicolaou colorations), with examples of nucleus extraction and classification.
We introduce here a new algorithm, called softSTAPLE, for computing estimates of segmentation generator performance and a reference standard segmentation from a collection of probabilistic segmentations of an image. These tasks have previously been investigated for segmentations with discrete label values, but few techniques exploit the information available in probabilistic segmentations. Our new...
In earlier work, we derived the dynamical behavior of a network of oscillatory units described by the amplitude and phase of oscillations. The dynamics were derived from an objective function that rewards both the faithfulness and the sparseness of representation. After unsupervised learning, the network is capable of separating mixtures of inputs, and also segmenting the inputs into components that...
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