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A Framework for Fish Species Identification, Freshness Assessment, and Formalin Detection
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 187 - Number 3 |
| Year of Publication: 2025 |
| Authors: B. Pavan Kalyan, Siddhant Kunde, Shreyas Simu, Varsha Turkar, Vaishab Jalmi |
10.5120/ijca2025924830
|
B. Pavan Kalyan, Siddhant Kunde, Shreyas Simu, Varsha Turkar, Vaishab Jalmi . A Framework for Fish Species Identification, Freshness Assessment, and Formalin Detection. International Journal of Computer Applications. 187, 3 ( May 2025), 40-47. DOI=10.5120/ijca2025924830
Abstract
Fish is most popularly consumed in coastal areas of India and some hinterlands as well, with demand increasing every year. To cater to this demand, fish must be transported to many metro cities and tourism-dominated areas. As a result, fish identification and fish freshness have become critical issues. Fish traders often store fish in cold storage with unapproved chemicals, such as formaldehyde, to extend storage life and prevent aging. However, this practice causes several health issues, including cancer. Additionally, the similarity in appearance of different fish species makes it difficult for consumers to identify the type of species. To confront this problem, this paper outlines the development of a fish identification and quality assessment system using Image Processing and Machine Learning (ML). The system can identify different fish species and detect fish freshness based on the number of days since the catch. Various feature extraction and machine learning classifier methods are applied to fish images for species identification and freshness assessment. Moreover, the paper introduces an approach to detect the presence of artificial formalin added to fish. The system, designed to be implemented on a mobile phone, combines software techniques with a hardware interface, including an HCHO sensor, to detect artificial formalin. This complete system is user-friendly and aims to enhance consumer safety by addressing both fish identification and the detection of harmful chemicals.
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