Real-Time Image Segmentation and Determination of 3D Coordinates for Fish Surface Area and Volume Measurement based on Stereo Vision

Jotje Rantung; Jong Min Oh; Hak Kyeong Kim; Sea June Oh; Sang Bong Kim

doi:10.5302/J.ICROS.2018.17.0213

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저널정보

제어로봇시스템학회
제어로봇시스템학회 논문지 학술저널
제어로봇시스템학회 논문지 제24권 제2호
2018.2 141 - 148 (8page)
DOI : 10.5302/J.ICROS.2018.17.0213

저자정보

Jotje Rantung (부경대학교)
Jong Min Oh (부경대학교)
Hak Kyeong Kim (부경대학교)
Sea June Oh (한국해양대학교)
Sang Bong Kim (부경대학교)

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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.

#real-time #image segmentation #object detection #camera calibration #3D coordinates #stereo vision