Automation of coastline detection

Coastline monitoring from video average images enables to assess erosion/accretion processes of a beach. Multiple calculation methods exist. Nevertheless, they often lack robustness to make it operational. To cope with this issue, Waves’n see has developed a technique of coastline’s automated detection, adapted to each study site. It is based on image segmentation by artificial intelligence and by k-means method. Then, a statistical analysis of coastline’s position maximizes the calculations’ confidence. This new methodology enables not only automated calculations, but also a coastline detection at least three times more efficient. In concrete terms, valid coastlines used to be obtained on 20 to 30% of images, whereas they are now obtained […]

Image stabilization

Video monitoring of coastal processes can be disturbed by camera movements. Whereas wind gust can cause high frequency movements, thermal dilation of the structure on which the camera sits on may cause daily frequency movements (see figure below). Horizon line position, characterized by a daily signal. In order to make a scientific use of our 4K images and videos (monitoring of coastline, beach topography, waves, bathymetry), we have developed and adapted image stabilization techniques to our needs. Two main cases are distinguished. In the first one, fixed elements in the image like windows and buildings edges are used as landmarks to register an image to an other. An improved version […]

WaveCams: the waves have arrived, where do they come from?

Today we change our perspective. In the previous posts about time-stack construction that allows us to estimate the period and height of the waves, we have always been looking at our beach in a one-dimensional cross-section. Today we will be looking at the waves in two dimensions. The wave direction plays an important role in multiple processes on the coast, it can drastically change the degree of exposure of our beach to storm events, changing the current’s direction and magnitude modifying sediment transport. In short, without an estimation of the direction in which the waves arrive at the coast, the hydro-morphological analysis would be incomplete. To illustrate, let’s travel to […]

WaveCams Time-Stack: Height, energy and more

Welcome back! Today will be our last post of the first WaveCams Time-stack trilogy. We recommend to review our previous posts before starting (What is a time-stack? and the “Time Dimension”). How do we know we can approach the beach safely? Intuitively, we know if the sea is agitated or not, it is easy to perceive the deafening noise of the waves or to notice the great amount of foam produced when big waves break! All the above phenomena are coming from the same process of energy conversion: the bigger the wave, the more energy it carries and therefore the more noise and foam it generates. The breaking of waves […]

WaveCams Time-Stack: The Time Dimension

Welcome to this new post! Today we will introduce the temporal dimension of our Time-stack, if you haven’t seen the explanatory video about this useful image yet I invite you to watch it here so you can better understand what we will see next. When we go to the beach and appreciate the waves our brain automatically interprets the differences in light (light and shadow) as waves that are directed towards us, so we manage to identify patterns on the surface of the sea. If we think about detecting the waves by remote devices, this shadow-light contrast is very useful and interesting to exploit. As we have seen in the […]