The invention discloses a method for detecting and identifying two insects in
water based on
deep learning, and relates to the technical field of aquatic biological detection.The method comprises the steps that
insect bodies are enriched through a micro-fluidic
chip,
DAPI / PI
dyeing is automatically completed, and recognizable biochemical
fluorescence characteristics are given to the
insect bodies;
dAPI, PI and bright field multichannel images are acquired through a
CMOS camera, and sub-pixel-level alignment of multispectral images is realized by using an
image registration and fusion
algorithm; denoising and segmenting the
multispectral image, extracting an
insect body area and enhancing the contrast; the positions of
polypide bodies are detected through an improved YOLOv8 model, and the activity states of the
polypide bodies are judged in combination with
fluorescence characteristics and form scores; counting the number of insect bodies and the live-to-dead ratio in real time, identifying capsules, and triggering live insect standard exceeding alarm and
pollution trend analysis; a model is deployed on an
edge device, an image uploading result is compressed, and
data security and
traceability are ensured through a block chain. The
system integrates
sample processing, imaging acquisition, intelligent identification and data feedback, and is suitable for long-time stable operation on site.