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Fish is a source of food for many species including human. It has been an important source of protein and other nutrients for human. Fresh fish are always better for preparing healthy and tasty food. Analysis of fresh fish is an important aspect to get the best quality of the fish for the preparation of healthy food. Sensory evaluation method is usually practiced in fish industry which involves judging of freshness by smell, color, appearance, taste and texture. The validity of this evaluation method has been questioned due to general parameters. In this study we are developing an evaluation method by using image processing of the fish eye. The fish eye image will be captured on different days and it is analyzed by using image processing tools to evaluate its freshness. The analysis will give the freshness index and classification of fish species used in this study. A series of fish images of different days is uploaded, the classification will be done and the result is presented in the excel sheet. In this study we use image processing tools to analyze the freshness of the sea fish. The analysis will be done on 2 species of fish. Initially the eye image of the fish is captured on different days and kept in the database. The images are segmented and its features are extracted. Classification of the image is done and a database is created as per the image captured on different days. KNN Algorithm is used for the classification. When a series of fish images are given as an input to the modeled device, it will crops its eye part, extracts the features and compares with the database. Fishes are classified into different grades and results are stored in the excel sheet to identify their grades. II. Proposed System The Proposed system consists of two stages. Stage one is to capture the images for creating database and in stage two a series of test images are given for classification based on database. In this system two species of fish, King Fish and Makrel are used for the freshness analysis. The images of two fish are captured and stored in day one. The process is repeated in day two, day three with the same setup. The required images are stored in the database. The eye part is extracted by image segmentation process and its features are obtained and stored in database. If a series of fish images of different days is given as the input for the model it will compare with the database and classify them according to their grades and the results are stored in the excel sheet. The block diagram of the proposed system is as shown below in Fig 1.

A Novel Idea for Freshness Analysis and Classification of Iced Sea Fish