Binary Text Images

Two kinds of binary text images are taken as examples, one handwritten text image and one typed text image, which are both typical synthetic images and widely used in many applications. Figure 4-15 gives a closer view of a part of the original and the watermarked handwritten text image. As shown in Figure 4-15 (a) and (b), the original and watermarked images look nearly identical to human observers, i.e. the watermark embedding process does not introduce noticeable artifacts. The difference between the original and the watermarked images is shown in Figure 4-15 (c). The flipped pixels are shown in black.

Figure 4-16 and Figure 4-17 present different kinds of manipulation tests and authentication results of a handwritten text image. In Figure 4-16, two kinds of

image respectively. First, the watermarked image was tampered by adding two zeroes at the end of the number “€500” to change it to “€50000”. Second, the text “Leo

€50000” was erased from the watermarked image. The third test is to combine the first and second alterations together. All these manipulations were done in Photoshop by simple copy, cut and paste operations. The altered versions look perfect and no noticeable trace is left on the image. The authentication and recovery result of every test is shown below the altered version. Two different kinds of manipulations are indicated in different colors: the deleted parts are indicated in red and the added ones in blue. From the result images, we can see that all the alterations are successfully detected and precisely localized. The deleted content is correctly recovered. Note that there are some blue dots in the red deleted parts and vice versa. These wrong color dots are caused by the unverified blocks that contain more than one altered pixels as we discussed in Section 4.4.

Another kind of manipulation, content replacement, is shown in Figure 4-17. The name

“Markus” was removed and replaced by “Stefan”. In this case, the added and deleted content are partly overlapped. The authentication and recovery result distinguishes the deleted name and the forged name successfully. The deleted name “Markus” is recovered in red color and the forged name “Stefan” is indicated in blue. It can be seen that in other areas there are still some noise-like red and blue dots that are not removed by the noise filter, but these noise dots do not affect the authentication result.

As we discussed in the previous sections, without noise filter the authenticator will give the highest sensitivity to any pixel manipulation. Figure 4-18 shows the above-mentioned four authentication results without noise filtering. All the red unverified pixels denote possible modifications from black to white, i.e. content deletion, while the blue unverified pixels denote possible modifications from white to black, i.e.

content addition. As shown in Figure 4-18, without any noise filtering, it is still very easy to distinguish different kinds of content manipulation. The altered content parts are successfully localized and recovered with higher sensitivity. For example, in Figure 4-18 (a), the deleted comma is partly overlapped with the added zero, so the actually

changed part is very small because the overlapped part remains in black. Despite the overlapping and small alternation, the authenticator gives a very accurate localization and recovery result as shown in Figure 4-18 (a). The overlapping part is shown in black, which means no modification, while the protruding parts of the deleted comma are shown in red to reveal the deletion. The added comma can also be recognized in blue color.

Besides the handwritten text image, Figure 4-19 presents an example of the typed text images, which is a part of typical electronic archive copy from the library. As shown in Figure 4-19 (a) and (b), the watermarked image achieves a very good visual quality and there is no noticeable difference between the original text image and the watermarked one. Figure 4-19 (c) gives a close view of a part of the watermarked image. In Figure 4-19 (d), the last word “way” is deleted and the period position is also shifted to left accordingly. The manipulation can be easily distinguished by comparing Figure 4-19 (c) and (d). However, without knowledge of the original version and only from the tempered version Figure 4-19 (d), the manipulation is very successful and completely unnoticeable. The authentication and recovery result is shown in Figure 4-19 (e), the deleted word “way” and the period are recovered in red color, while the faked period is also marked out in blue color.

Figure 4-15 Close view of a part of watermarked image: (a) Original image, (b) Watermarked image, (c) Difference image, flipped pixels are shown in black.

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(b)

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Figure 4-16 Handwritten text image test: content removal and addition. Left:

watermarked image; Right: original version, different tampered versions and authentication results. Two zeros “00” is added at the end of “€500” and the text “Leo

€5000” is deleted respectively. The detected result indicates the manipulations in different color: blue for addition and red for removal.

Authentication and recovery result Content deletion

Authentication result Content addition Original version

Addition and deletion

Authentication and recovery result Blue color indicates added

characters, and red color indicates deleted ones.

Figure 4-17 Handwritten text image test: content replacement. Left: watermarked image; Right: original version, tampered version and authentication result. The name

“Markus” is replaced by “Stefan”. The authentication result indicates the deleted

“Markus” in red color while the forged “Stefan” in blue color.

Original version

Content replacement

Authentication and recovery result

Blue color indicates added characters, and red color indicates deleted ones.

Figure 4-18 Authentication results without noise filter. (a) Content addition, (b) Content deletion, (c) Combination of content addition and deletion, (d) Content replacement. The red unverified pixels denote possible modifications from black to white, i.e. content deletion, and the blue pixels denote possible modifications from white to black, i.e. content addition.

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(b)

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Figure 4-19 Binary typed text image test: content removal and addition. (a) Original text image, (b) Watermarked text image, (c) Part of the watermarked map, (d) Tampered version: the last word “way” is deleted and the period is then shifted to left.

(e) Authentication and recovery result: the deleted word “way” and period are indicated in red color and the added period in blue color.

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(b)

(c) (d) (e)