明慧--Introduction(cont. 2)

The textured-textual-image-based mechanism we proposed is more difficult to defeat since it involves two challenging problems in computer vision, namely, image segmentation and texture analysis. It cleverly makes use of the unique capabilities of human visual systems such as filling-in of contours. The result is a more robust and temper-resistant scheme for access control.

我們所提出的以影像貼圖為基礎的手法，自從包含影像分割及貼圖分析這兩種問題後，已經變得較難破解了，他是利用人類視覺系統的獨特能力去填滿影像，此結果在存取控制上為一份更具磨練性的計畫。


In this paper, we carry on the same principle: gestalt theory, to devise another visual CAPTCHA which is also easy to generate, yet tough to defeat. The test in the newly developed method is formed simply by exchanging non-overlapping blocks in an image. Passing the test requires clicking on the switched regions with the pointing devices, a more natural way to interact than keyboard entry if the user is mostly doing the browsing.

在這篇論文中，我們持續在相同的原則上：型態理論，構想另外一種視覺上的CAPTCHA，容易產生更容易破解。這項測試在近年來的發展是在一張影像當中交換非重複的區塊，通過在被要求點擊交換區塊的測試，而不是使用鍵盤輸入，為一個使用者在瀏覽網頁時更自然的互動方式。


The rest of this paper is organized as follows. In section 2 we formally present the algorithm to generate the test and justify its efficacy in telling humans and machines apart. We will also discuss issues regarding the choice of parameters and image database. Section 3 describes possible ways to defeat the proposed CAPTCHA and our corresponding counter-measures. Section 4 presents the experimental results of applying several image segmentation techniques to identify the exchanged blocks. Section 5 concludes this paper with a short conclusion and outlines possible improvements and future developments.

以下介紹這篇文章的架構。在第2章我們完整地描述演算法去測試這實驗，並且證明在人機辨識系統中式有效的，也討論關於特徵及影像資料庫選擇的問題。在第3章描述可能破解我們所提出的CAPTCHA方法和對應的相關措施。第4章提出幾個影像分割技術的實驗結果，用來辨識已經交換的區塊。第5章簡單敘述結論，以及提出未來可能的發展和改進的方向。