Current web-based search engines (such as Google or Yahoo) do not provide adequately for the search of personal data (including personal facial image, address, telephone number, etc.). If a user inputs a person?s name to a search engine, he/she may need to spend much time in finding the desired data from those returned by the search engine. In this research, we propose to find personal data based on an image search engine. A person?s name is used in the study as a query. After a user inputs a query, we call Google image search engine and obtain related images from Google. Three approaches are also proposed to rank images returned by Google such that the user may find the desired personal data from the fronter images. In the first proposed approach, we analyze for each image the string of words which is also returned by Google and then obtain a ranking score. The images are ranked based on the scores. Images with large scores are ranked in front. In the second method, we re-rank images based on the number of frontal faces in each image. Images with only one face are ranked at the front, and then images with two, three, and more faces are ranked. In the third method, we link to each web page on which an image returned by Google is put, and analyze the text on the web page. If the text has more key words about personal data, the image is ranked at fronter locations. Users may select one of the three approaches accordiny to their requirement in response time. Experimental results show the feasibility of the proposed approach.
