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SFTA와 AdaBoost 기반 한우의 육질 등급 분석

Grading meat quality of Hanwoo based on SFTA and AdaBoost

  • 조현학 (부산대학교 로봇관련협동과정) ;
  • 김은경 (부산대학교 전기전자컴퓨터공학과) ;
  • 장은석 (부산대학교 전기전자컴퓨터공학과) ;
  • 김광백 (신라대학교 컴퓨터정보공학부) ;
  • 김성신 (부산대학교 전기전자컴퓨터공학과)
  • Cho, Hyunhak (Department of Interdisciplinary Cooperative Course: Robot, Pusan National University) ;
  • Kim, Eun Kyeong (Department of Electrical and Computer Engineering, Pusan National University) ;
  • Jang, Eunseok (Department of Electrical and Computer Engineering, Pusan National University) ;
  • Kim, Kwang Baek (Department of Computer and Information Engineering, Silla University) ;
  • Kim, Sungshin (Department of Electrical and Computer Engineering, Pusan National University)
  • 투고 : 2016.11.21
  • 심사 : 2016.12.14
  • 발행 : 2016.12.25

초록

본 논문에서는 한우의 근내 지방 부분을 초음파 기기를 이용하여 촬영한 초음파 영상의 특징 분석을 통해 classification 알고리즘을 이용하여 한우의 도체육질 등급을 예측하는 방법을 제안하며, 인체의 초음파 영상을 이용하여 진단 및 치료 검증 과제에 있어 사전 연구로 진행된 연구로, 차후에는 초음파 영상의 분석 범위를 확대할 예정이다. 한우의 초음파 영상을 활용한 경우에는 생체 정보를 한우 개량의 측면에서 생체 육질 정보를 조기에 획득하여 활용함으로써, 도축하지 않고도 육질 및 육량을 측정하여 개량의 속도를 배가시킬 수 있고, 농가 경영 측면에서 출하시기 및 방법의 조절로 농가 수익향상에 일조할 수 있는 중요한 핵심 기술이다. 이에 대한 많은 연구가 미국과 일본을 중심으로 이루어져 왔으며, 특히 기기에 의한 객관적인 측정방법들이 다양하게 연구되고 있지만 정확도가 낮다. 따라서 제안된 연구에서는 한우의 근내 지방 초음파 영상에 특징점 추출 알고리즘과 classification 알고리즘을 적용하여 한우의 도체 육질을 예측하였다. 실험 결과 제안하는 방법을 적용하였을 경우, 기존의 방법에 비해 효율적인 것을 확인할 수 있었다.

This paper proposes a grade prediction method to measure meat quality in Hanwoo (Korean Native Cattle) using classification and feature extraction algorithms. The applied classification algorithm is an AdaBoost and the texture features of the given ultrasound images are extracted using SFTA. In this paper, as an initial phase, we selected ultrasound images of Hanwoo for verifying experimental results; however, we ultimately aimed to develop a diagnostic decision support system for human body scan using ultrasound images. The advantages of using ultrasound images of Hanwoo are: accurate grade prediction without butchery, optimizing shipping and feeding schedule and economic benefits. Researches on grade prediction using biometric data such as ultrasound images have been studied in countries like USA, Japan, and Korea. Studies have been based on accurate prediction method of different images obtained from different machines. However, the prediction accuracy is low. Therefore, we proposed a prediction method of meat quality. From the experimental results compared with that of the real grades, the experimental results demonstrated that the proposed method is superior to the other methods.

키워드

참고문헌

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