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Stereo image segmentation with application in underwater fish detection and tracking

机译：立体图像分割及其在水下鱼类检测和跟踪中的应用

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Most often, background subtraction and image segmentation methods use images or video captured using a single camera. However, segmentation can be improved using stereo images by reducing errors caused due to illumination fluctuations and object occlusion. This work proposes a background subtraction and image segmentation method for images obtained using a two camera stereo system. Stereo imaging is often employed in order to obtain depth information. On the other hand, the objective of this work is mainly to extract accurate boundaries of objects from stereo images, which are otherwise difficult to obtain. Improving the outline detection accuracy is vital for object recognition applications. An application of the proposed technique is presented for the detection and tracking of fish in underwater image sequences. Outline fish detection is a challenging task since fish are not rigid objects. Moreover, color is not necessarily a reliable means to segment underwater images, therefore, grayscale images are used. Due to these two reasons, and due to the fact that underwater images captured in non-controlled environments are often blurry and poorly illuminated, commonly used local correlation methods are not sufficient for stereo image matching. The proposed algorithm improves segmentation in several scenarios including cases where fish are occluded by other fish regions. Although the work concentrates on segmenting fish images, it can be employed in other underwater image segmentation applications where visible-light cameras are used.
机译：大多数情况下，背景减影和图像分割方法使用的图像或视频是使用单个摄像机捕获的。然而，可以通过减少由于照明波动和物体遮挡而引起的误差来使用立体图像来改善分割。这项工作提出了一个背景减法和图像分割方法，用于使用两相机立体系统获得的图像。为了获得深度信息，经常采用立体成像。另一方面，这项工作的目的主要是从立体图像中提取物体的准确边界，否则很难获得。对于物体识别应用而言，提高轮廓检测精度至关重要。提出了所提出的技术在水下图像序列中对鱼的检测和跟踪的应用。由于鱼类不是刚性物体，因此轮廓鱼类的检测是一项艰巨的任务。而且，颜色不一定是分割水下图像的可靠手段，因此，使用了灰度图像。由于这两个原因，并且由于在不受控制的环境中捕获的水下图像通常模糊且照明不佳的事实，常用的局部相关方法不足以进行立体图像匹配。所提出的算法在包括鱼被其他鱼区域遮挡的情况在内的几种情况下提高了分割效果。尽管这项工作专注于分割鱼图像，但是它可以用于使用可见光相机的其他水下图像分割应用中。

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