Moving target classification and tracking from real-time video

A Pump Based Microfluidic Image Processing System for Droplet Detection and Counting

“…One of the challenges towards continuous flowing droplet detection and counting certainly is the motion detection by detecting the intensity difference of droplets contrary to the channel background [9]. While in most cases droplets have particular transparency, their particular images do not offer high intensity difference, i.e., contrast, contrary to the background.…”

“…The variation in the background brightness and darkness directly affects the contrast. In our work, an efficient motion detection technique based on temporal difference is developed for the flowing droplet counting and detection in a series of frames [9,10]. Taking into account the intensity characteristics of droplet images, there are actually two steps required.…”

The Sakbot System for Moving Object Detection and Tracking

“…These systems obviously differ in the approach proposed, but also in various assumptions about the operational environment. One first main distinction is between systems adopting a single, fixed camera [1][2][3][4][5][6] with respect to systems adopting either multiple cameras [7] or an airborne camera [8]. In this work, we focus on a single fixed camera scenario, since it still captures a wide spread of applications.…”

Robust Edge-Enhanced Fragment Based Normalized Correlation Tracking in Cluttered and Occluded Imagery

“…Since the correlation [1,3] process does not lose the spatial information of the pixels, they are more robust to clutter than the histogram based trackers. Edge Enhanced Normalized Correlation (EENC) tracker [5] has significantly solved the real-world problems of orientation, illumination, obscuration, intermittent occlusion, complex object motion, object fading, and noise.…”