LIGHTING CONTROLLER FOR SEA LICE DETECTION
Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for a lighting controller for sea lice detection. In some implementations, a pulse of red light and a pulse of blue light can be timed with the exposure of a camera to capture multiple images of a fish or group of fishes in both red and blue light. By using the captured images with different color light, computers can detect features on the body of a fish including sea lice, skin lesions, shortened operculum or other physical deformities and skin features. Detection results can aid in mitigation techniques or be stored for analytics. For example, sea lice detection results can inform targeted treatments comprised of lasers, fluids, or mechanical devices such as a brush or suction.
1 . A method comprising:
illuminating a red light at a first time;
illuminating a blue light at a second time;
controlling an exposure of a camera to generate a first image of a fish illuminated by the red light;
controlling the exposure of the camera to generate a second image of the fish illuminated by the blue light; and
providing features of the first image and the second image to a processing model.
2 . The method of claim 1 , comprising:
determining whether the fish is likely affected by a particular condition based on an analysis of at least the first image and the second image.
3 . The method of claim 2 , wherein the particular condition comprises a marine parasite infection, an occurrence of a lesion, or a physical deformity.
4 . The method of claim 1 , wherein the fish is contained within a fish pen or a fish run.
5 . The method of claim 1 , wherein a peak power of the blue light is within a wavelength range of 450 nanometers to 480 nanometers.
6 . The method of claim 1 , wherein a time between illuminating the fish with the red light and illuminating the fish with the blue light is less than 0.2 seconds.
7 . The method of claim 1 , comprising not illuminating the blue light at the first time and not illuminating the red light at the second time.
8 . The method of claim 1 , wherein machine learning informs illuminating the fish or generating the first image or the second image if the fish.
9 . The method of claim 1 , wherein machine learning informs parasite detection on the fish based on one or more of the first image and the second image.
10 . The method of claim 1 , comprising storing the first image and the second image in an image buffer.
11 . A computer-implemented system, comprising:
one or more computers; and
one or more computer memory devices interoperably coupled with the one or more computers and having tangible, non-transitory, machine-readable media storing one or more instructions that, when executed by the one or more computers, perform one or more operations comprising:
illuminating a red light at a first time;
illuminating a blue light at a second time;
controlling an exposure of a camera to generate a first image of a fish illuminated by the red light;
controlling the exposure of the camera to generate a second image of the fish illuminated by the blue light; and
providing features of the first image and the second image to a processing model.
12 . The system of claim 11 , comprising:
determining whether the fish is likely affected by a particular condition based on an analysis of at least the first image and the second image.
13 . The system of claim 12 , wherein the particular condition comprises a marine parasite infection, an occurrence of a lesion, or a physical deformity.
14 . The system of claim 11 , wherein the fish is contained within a fish pen or a fish run.
15 . The system of claim 11 , wherein a peak power of the blue light is within a wavelength range of 450 nanometers to 480 nanometers.
16 . The system of claim 11 , wherein a time between illuminating the fish with the red light and illuminating the fish with the blue light is less than 0.2 seconds.
17 . The system of claim 11 , comprising not illuminating the blue light at the first time and not illuminating the red light at the second time.
18 . The system of claim 11 , wherein machine learning informs illuminating the fish or generating the first image or the second image if the fish.
19 . The system of claim 11 , wherein machine learning informs parasite detection on the fish based on one or more of the first image and the second image.
20 . A non-transitory, computer-readable storage medium storing one or more instructions executable by a computer system to perform operations comprising:
illuminating a red light at a first time;
illuminating a blue light at a second time;
controlling an exposure of a camera to generate a first image of a fish illuminated by the red light;
controlling the exposure of the camera to generate a second image of the fish illuminated by the blue light; and
providing features of the first image and the second image to a processing model.