# A Review on Observer Assistance Systems for Harvested and Protected Fish Species
## 4 Experiments on Electronic Monitoring Systems  
This section provides an explanation of the proposed system and the simple experimental contents of the transmission module, as well as the experimental contents of the Image Segmentation Manager. The reason why the Image Segmentation Manager was applied to this study is the same as the problem of determining the limited size of blobs mentioned in Section 3. As for the limited size of the blob, there is no problem when the size of the image to be estimated matches the width and height, such as the existing 320 \(\times\) 320, 412 \(\times\) 412, and 832 \(\times\) 832 images. However, image sensors in real environments are diverse, and thus the size is delivered in various ways. That is, the aspect ratio of the image received from the image sensor is generally 4:3; therefore, the horizontal and vertical sizes are not the same. However, most of the images used in the object detection have the same horizontal and vertical images. Learning is also undertaken in the same situation as the horizontal and vertical, and the blob size is fixed. Figure 3 shows the state in which the blob is cropped and the state in which it is not. In other words, cropped means that other images around it are lost. However, if it remains uncropped, it is evident that the aspect ratio is estimated at 1:1. Figure 3(a) shows the estimation of a person in a cropped state, and Figure 3(b) shows the estimation of a person in an uncropped state. Figure 3(c),d show cropped and uncropped images for a fish, respectively. Figure 3: A comparison of cropped and uncropped images. There is a problem of showing errors in estimation, but there is also a problem that the box does not accurately represent the object. In particular, when estimating in (c) and (d), the weights [73] provided by previous studies were used. It is evident that most of the weights are trained appropriately for the image or video presented in each study. Additionally, a merged weight that combines the weights of deepfish and ozfish [73] is proposed, but if the environment does not match, it is evident that there is an error in the estimation. Figure 5 is a conceptual diagram of the image segmentation estimation technique. In the image collector, a real-time video is continuously recorded and transmitted in units of 1000. The network distributor and image decomposer in the prediction server proceed when the image arrives. Figure 4: A comparison of predicted images after setting up the cropped and uncropped images: (**a**) cropped image for a person; (**b**) uncropped image for a person; (**c**) cropped image for a fish; (**d**) uncropped image for a fish. Figure 5: A conceptual diagram of the image segmentation estimation technique. The network distributor opens as many port numbers as the number of images. The image decomposer divides the image by the size confirmed in the decision and performs object detection through each communication port. The reason why ports are used is to classify and manage image information by port number without losing image information in the process of delivering images of various sizes. Therefore, in a method to solve this problem, an image segmentation estimation technique is proposed. The image segmentation estimation technique is shown in Figures 5 and 6. As shown in Figure 6, the image collected in real time is divided into four parts to perform object detection. It can be seen that an object that was not previously detected is detected. Additional results are shown in Figure 7.  
Figure 8 is the result of four divisions once more. However, there is a problem that the pixel resolution is lowered, and boxing does not accurately mark the object. In addition, the overall selection problem and object recognition accuracy are low. Figure 6: Prediction results for the first quadrant image. Figure 7: Details of prediction results for the first quadrant image. If it results in added learning about the object, an estimation suitable for the current situation will be possible.