스테리오 비젼에 기반한 어류 표면적과 부피 측정을 위한실시간 영상 분리와 3D 좌표의 결정 (Real-Time Image Segmentation and Determination of 3D Coordinates for Fish Surface Area and Volume Measurement based on Stereo Vision)

서지정보

· 발행기관 : 제어·로봇·시스템학회
· 수록지 정보 : 제어.로봇.시스템학회 논문지 / 24권 / 2호 / 141 ~ 148페이지
· 저자명 : Jotje Rantung, 오종민, 김학경, 오세준, 김상봉

초록

This paper proposes the real-time image segmentation and determination of 3D coordinates for fish surface area and volume measurements based on stereo vision. The segmentation process is performed in real-time on the video frame. Complexity and computation time are reduced by segmenting hue and value feature spaces separately before combining result. Morphological erosion and morphological dilation are applied to remove any object pixels that are clustered as background pixels. Finally, image segmentation is obtained in the binary image of an object. A step-by-step approach to computing a binary image is applied to obtain segmentation image. The object is considered a fish on a platform with a known background color, a known geometric shape for the fish, and the stereo camera is in fixed position to capture an image. The objective of this paper is to obtain a simple but accurate 3D image that is capable of capturing the 3D coordinates values of the fish object. The followings are done for this task: First, the stereo camera is calibrated to collect its intrinsic parameters and distortion parameters correctly. Second, an image is captured by the camera, that is segmented in real-time to distinguish between the object’s destination and its surroundings. Finally, the object coordinates, surface area, and volume of the fish are measured. Experiment results show that the proposed method has good results in real-time segmentation, and shows different surface areas and volumes within about 6% and 5.3%, respectively.

영어초록

This paper proposes the real-time image segmentation and determination of 3D coordinates for fish surface area and volume measurements based on stereo vision. The segmentation process is performed in real-time on the video frame. Complexity and computation time are reduced by segmenting hue and value feature spaces separately before combining result. Morphological erosion and morphological dilation are applied to remove any object pixels that are clustered as background pixels. Finally, image segmentation is obtained in the binary image of an object. A step-by-step approach to computing a binary image is applied to obtain segmentation image. The object is considered a fish on a platform with a known background color, a known geometric shape for the fish, and the stereo camera is in fixed position to capture an image. The objective of this paper is to obtain a simple but accurate 3D image that is capable of capturing the 3D coordinates values of the fish object. The followings are done for this task: First, the stereo camera is calibrated to collect its intrinsic parameters and distortion parameters correctly. Second, an image is captured by the camera, that is segmented in real-time to distinguish between the object’s destination and its surroundings. Finally, the object coordinates, surface area, and volume of the fish are measured. Experiment results show that the proposed method has good results in real-time segmentation, and shows different surface areas and volumes within about 6% and 5.3%, respectively.

참고자료

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