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The detection and tracking of moving object is the important research of image analysis and understanding as well as in computer vision field, and have extensive application in the traffic monitoring, the military, industrial process control and medical research, but less application in the underwater monitoring of fish. In this paper, in order to be able to real-time detection of the fish in the digital video system moving target, proposed the fish moving target detection algorithm under a camera. With an improved background updating method of adaptive Gaussian mixture model, a method to detect the target fish based on Gaussian mixture model combined with edge detection operator.

When we read data from our fish finder, we usually imagine that the information we see on our screen is all happening directly under our sonar. So, if we see a fish on the screen, we think it must be exactly underneath our sonar. In reality, the readings we see are taken from a wider area underneath our sonar. And even more importantly, the sonar receives data from a wider and wider area, the deeper you scan. This is all because sonars scan in cones.

When we read data from our fish finder, we usually imagine that the information we see on our screen is all happening directly under our sonar. So, if we see a fish on the screen, we think it must be exactly underneath our sonar. In reality, the readings we see are taken from a wider area underneath our sonar. And even more importantly, the sonar receives data from a wider and wider area, the deeper you scan. This is all because sonars scan in cones.

Surface clutter appears because the water close to the surface will reflect some of the sonar waves, and these reflections are much too fast for the sonar to process correctly. This reflection has numerous causes, the most common being waves on the surface, bubbles, currents and algae. The result is lots of close to the surface. This creates a in which it is not possible to identify fish. The amount of clutter, and the size of this blind zone, can be reduced if the sonar frequency is higher. So, if you have a Deeper PRO or PRO+ and you are experiencing a lot of surface clutter, switch to scanning with the higher frequency(Narrow beamat 290kHz 15). In the case of the Deeper START, its 120 kHz sonar frequency means surface clutter can reach down to 1 meter / 3.3 ft. below the surface of the water.

Surface clutter appears because the water close to the surface will reflect some of the sonar waves, and these reflections are much too fast for the sonar to process correctly. This reflection has numerous causes, the most common being waves on the surface, bubbles, currents and algae. The result is lots of close to the surface. This creates a in which it is not possible to identify fish.

The image below illustrates 2 different situations where surface clutter can affect your sonar readings – (in these examples the surface clutter extends to approximately 1 meter / 3.3 ft. below the surface):The fish is below thesurface clutterzone. In this scenario, the sonar reflection from the fish is strong enough to be identified by the fish finder (in the case of Deeper fish finders, the FishDeeper App uses an algorithm to work out if it`s a fish). As a result, the fish is displayed on the app.The fish is within thesurface clutterzone. The sonar reflection from this fish is mixed together with the surface clutter, making it too weak to be identified by the fish finder. As a result, the fish is not displayed on the app.

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