In this paper, we present algorithms based on image processing and machine learning techniques to determine the size of a chicken egg from an egg image taken by an Android mobile device. While the constraint on this study was the need to refer to the domestic environment, the proposed techniques could be up-scaled and become useful in a large-scale industrial application. The simplicity of this approach, in terms of necessary lighting, egg positioning and other factors also makes t relevant as a possibly cheaper but still effective industrial application.
The rest of the paper is organized as follows: First, in Section II, a literature review on egg inspection is discussed. Next, in Section III, we describe the proposed algorithms in details. In Section IV, performance comparison experiments and results are presented to evaluate the efficiency of our algorithm. Finally, Section V gives the conclusion of this study.
System Overview A user can use our system by placing a sample egg on a sheet of white paper or any white or near white background. The egg must have a brown colored shell to provide sufficient contrast. Then, the user takes a photo of the egg with our app using the Android device’s camera. The app calculates the size of the egg and returns the result to the user. Since the mobile device can be positioned over the egg at an arbitrary distance when taking a photo, a dimension reference needs to be visible in the acquired image to provide a dimension reference for the egg. Our system is designed to use a coin as the reference object because coins are common, and have known sizes. Thus, the user places a coin alongside the egg and take a photo of both, side-by-side. Given that we are in Thailand, the system works with a One-Baht or a Five-Baht coin as a reference object. Our system also allows a customization of the reference coin size in order to use other coinage. Fig. 1 shows a block diagram which illustrates the underlying algorithm. The algorithm for egg size classification includes two main parts, the coin image analysis, and the egg image analysis. The main purpose of the coin image analysis is to find a coin in the acquired image and measure the dimensions of the coin in the image, which will vary depending on the distance from which the image was taken. This part consists of the coin detection, the coin image segmentation, the measurement of coin dimensions, and the pixel size computation. CodeShoppy
We have developed egg size classifIcation algorithms based on image processing and the SVM classifIer. The robustness of this approach allows the system to work well in more naturalistic settings such as domestic environments. The experimental results showed that our segmentation techniques can extract relevant information with small errors, and our classifIcation technique can classify egg size with accuracy of 80.4%. Further work includes improving the fItting algorithm; instead of fItting an egg with an ellipse, an oval should give more accurate results. While the focus of this study was the classifIcation using an image taken with an Android device in the household or market environments, the proposed algorithms could be modifIed and applied in an automatic large-scale egg industrial application.