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Sử dụng xử lý ảnh bằng Opencv ước lượng chiều dài và cân nặng của cá dẹt Hàn Quốc. Chiều dài của cá được xử lý thông qua hình ảnh được chụp từ camera. Mối quan hệ chiều dài và cân nặng được tạo ra để ước lượng kích thước cá. Slide được làm bằng ngôn ngữ tiếng anh.
Real-time estimation of the length and body weight of olive flounder in Indoor Aquaculture Farms Using Visual Information • Nguyen Thi Phuong Hang • Company: Lucas CONTENTS I Project description II Environmental system III Estimation method IV Result V Application VI Discussion Project description Company partner: Lucas Motivation: + For saving feed and labor, the cost + Reducing water pollution during starvation, and improving feeding activity and feed efficiency shortly after refeeding + Achieving compensatory growth of fish Þ Support the harvest, and optimize the farm management Purpose: + Develop image-based olive flounder length measurement + Estimate the body weight based on the length with the length-weight relationship II Experimental environment and system Environmental system A water tank (2300 × 1195 × 1200 mm, 3.3 m3) A 5×5 cm grid cameras Experimental conditions for image data acquisition (top) And Left-side and right-side phone captures of the training environments (bottom) Data acquisition The system includes: • A water tank (2300 × 1195 × 1200 mm, 3.3 m3) with a × cm grid bottom created by the black vertical lines and the black horizontal lines • cameras at the top of the tank to capture the image • The experiment was performed with 90 olive flounders • First, the fish were anesthetized in a solution to losing consciousness then they were put on an electronic scale and a measuring board to acquire the accurate weight and length as the actual length (cm) and weight (g) Dataset + The dataset (1600x900) includes 180 images taken + After we get the reference object, we can use the system to estimate length without the 5x5 grid Estimation method Estimation algorithm Captured images Detect Contours Detect extreme points Calculate the distance between extreme points Find the max distance – pixel length Cameras Training environment (reference object) Lagrange's interpolation formula Length in cm Lagrange’s interpolating formula Lagrange’s interpolating polynomial is an algorithm that can construct a polynomial that passes through any desired set of points and is represented as follows: Here, polynomial of degree passes through points (x1, y1 = f(x1)),(x2, y2 = f(x2)), …, (xn, yn = f(xn)) 𝑛 𝑘 𝑗 ¿𝑘=1 𝑗 𝑘 ¿𝑘 ≠ 𝑗 𝑃𝑗 ( 𝑥 ) = 𝑦 ∏ 𝑥−𝑥 𝑥 −𝑥 Results Results of Reference environment (reference object to convert from pixel to real length (cm) The result of the estimated fish length and t he table summarize the mean, SD (standard deviation), R-square, and MSE (Mean squared error) for evaluating estimated results Result of length-weight relationship Mass estimation models were created using two basic mathematical relationships: Weight = a(length)b + c Result of the estimated regression equation between the length and the body weight of fish (left) and the comparison of estimated data with surveyed data (right) Application Build with Streamlit framework DEMO VIDEO DISCUSSION AND CONCLUSION + The algorithm proposed with high accuracy (R-squared = 0.994) + The length-weight relationship generate to support estimating the body weight of fish, and the length-weight model with high accuracy (R-squared = 0.91) + The overlapping is a limitation + Future work: object detection with a Deep learning model rotated the bounding box will increase the accuracy of length THANK YOU FOR LISTENING