The fish is sick, SingTown Technology OpenMV knows first.

In aquaculture and ornamental fish management, common diseases such as fish skin diseases, fin and tail rot, and water mould disease, if not detected in time, will severely affect the health and survival rate of fish populations. Traditional detection primarily relies on manual visual observation, which is not only inefficient but also easily interfered with by turbid water, changes in lighting, and fish movement, making it difficult to accurately assess pathological conditions promptly.

To this end, aquaculture enterprises have adopted SingTown Technology's OpenMV intelligent camera to establish a machine vision-based fish health monitoring system for real-time identification of abnormalities on fish surfaces. The system is installed on the outer glass walls of fish tanks or aquaculture ponds, capable of monitoring fish activity within a range of one metre, and performing automatic identification and lesion detection on small goldfish approximately five centimetres in length.

The system's objective is to determine, through image recognition, whether pathological features such as white spots, white fuzz, water mould, or fin rot appear on the fish's body surface. This provides early-stage health warnings and assists breeders in taking timely action.

Aquaculture enterprises utilise the SingTown intelligent camera system to construct a fish health identification system, integrating AI image recognition, colour segmentation, texture analysis, and feature comparison algorithms, enabling accurate detection of fish body lesions underwater.

The system captures real-time images of the aquarium via a high-definition camera. On the edge side, AI utilises a colour recognition algorithm to extract the fish body area and filter out background reflected light. The algorithm then identifies abnormal reflective areas, such as white spots or water mould, by analysing the brightness distribution and texture continuity on the fish body surface. Simultaneously, the algorithm can assess the presence of fin rot, fin decay, or mould attachment by combining morphological features, such as irregular fin edges, local whitening, or blurring.

To accommodate the movement of fish in water and fluctuations in light, the system incorporates dynamic threshold adjustment and multi-frame fusion algorithms, providing stable judgment for short-term consecutive images and effectively reducing false alarms. During testing, with the recognition distance controlled within 1 metre, the system can simultaneously identify multiple individuals, achieving an accuracy rate exceeding 92% in detecting water mould disease in small fish such as goldfish. Detection results can be output in real-time to the host computer or APP, with alerts for suspected lesions sent via the network.

SingTown OpenMV intelligent camera is easy to operate, has low power consumption, and offers strong real-time detection capabilities. It is suitable for deployment on edge devices in aquaculture, pet aquariums, and university research laboratories, helping users achieve timely, visual, and intelligent monitoring of fish health.