The evaluation results of a system for tracking humans in surveillance videos are presented. Moving blobs are detected based on adaptive background modeling. A shape based multi-view human detection system is used to find humans in moving regions. The detected responses are associated to infer the human trajectories. The shaped based human detection and tracking is further enhanced by a blob tr...

This study uses Blob Analysis technique to optimize Gaussian Mixture Model method performance in detecting and counting cars and motorcycles under heavy traffic conditions. It is profound that by optimizing the minimum and maximum blob area in order to obtain proper blob size from a video image’s region of interest will also improve the accuracy of system. The result shows that appropriate para...

This paper discusses automatic Transmission Electron Microscopy (TEM) image registration, TEM slice assembly via tile mosaicking, and TEM volume assembly via slice to slice registration. Several algorithms are presented, including an algorithm for mosaic layout of an unordered set of tiles, an algorithm for distortion correction, and an image processing algorithm for a coarse edge and blob dete...

This paper presents a novel MoG based method for foreground detection and segmentation in video surveillance. Normal MoG is different to deal with the foreground objects that stay in the scene for a long time and segment difficult foreground objects from one blob. We improve MoG by adopting posterior feedback information of Kalman filter tracking, to robustly modeling the background and to perf...

This paper presents a new method for automatic quantification of ellipse-like cells in images, an important and challenging problem that has been studied by the computer vision community. The proposed method can be described by two main steps. Initially, image segmentation based on the k-means algorithm is performed to separate different types of cells from the background. Then, a robust and ef...

A new family of symbolic compression algorithms has recently been developed that includes the ongoing JBIG2 standardization effort as well as related commercial products. These techniques are specifically designed for binary document images. They cluster individual blobs in a document and store the sequence of occurrence of blobs and representative blob templates, hence the name symbolic compre...

This paper presents a novel, real-time defect detection system, based on a best-fit polynomial interpolation, that inspects the conditions of outer surfaces. The defect detection system is an enhanced feature extraction method that employs this technique to inspect the flatness, waviness, blob, and curvature faults of these surfaces. The proposed method has been performed, tested, and validate...

This paper presents the evaluation results of a system for tracking humans in surveillance videos. Moving blobs are detected based on adaptive background modeling. A shape based multi-view human detection system is used to find humans in moving regions. The detected responses are associated to infer the human trajectories. The shaped based human detection and tracking is further enhanced by a b...

The Laplacian-of-Gaussian (LoG) (lter is an optimal edge detector, but it is computationally ine3cient. In this paper, we propose the bilevel Laplacian-of-Gaussian (BLoG) (lter to approximate the LoG (lter. This approximation is formulated as an optimization problem and solved by the gradient descent algorithm. Only two multiplications per pixel are required in convolving with the BLoG (lter. T...

Deep convolutional neural networks (CNN) have proven to be remarkably effective in semantic segmentation tasks. Most popular loss functions were introduced targeting improved volumetric scores, such as the Dice coefficient (DSC). By design, DSC can tackle class imbalance, however, it does not recognize instance imbalance within a class. As result, large foreground dominate minor instances and s...