Using Edge Detection to Object Proposal and Detection ─ A case study of drink commodity

Nowadays as the social media progresses, more people are starting to use photosin their social media website to share the events in their daily lines. These photos often contain people and things occurring in their lives, which can be used as the data for our information analysis. In order to collect information from these photos, in the past the used information are words, but since recently the field of image detection has made an improvement, the usage of image analysis technology becomes more widely applied on this field to mine the information from the image. In this paper, the method is based on the edge detection to be as a new way of object proposal. We use the drinks products as medium to select the assumed candidates from the drink image of database, and using SIFT to derive the characteristics of the objects. After the characteristics are decided, we use SVM to categorize the drinks from their image mark. The essay is divided into two parts, the object proposal and the object detection. First, we collect a variety of pictures containing the commodity of the drinks from the internet and the pictures taken. Then, through the method of edge detection we get the edges of the objects. As the edges are found, we look for the closed regions in the picture, and use the filter made by the characteristics got from the statistic data to filter these areas to find the possible region locating the objects marked as candidates. Finally, we apply SIFT method on these region candidates to get the characteristic description and use SVM to make predicts of classification.