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1. Technical Field
The invention relates generally to image processing technology. More particularly, the invention relates to a process and method for algorithmic determination of image transparency.
2. Description of Prior Art
When extracting images from another program, transparency needs to be handled correctly because the transparent portion of the images may change to another color during transformation.
One solution is to analyze each byte of the two input images directly in the visual basic code, but that is too slow. The alternative solution is to make use of the bitmap operations, which are faster, by setting the transparent portions of the images to white during the extraction process. This solution is still problematic because when making all white pixels transparent, any pixels that were white in the original image will be also changed to be transparent in the exported image.
What is desired is to develop a process for determining transparency of exported images wherein transparency is not shown where it should not be shown.
A method for determining transparency in image extraction creates a first mask bitmap by combining a first image and a second image, wherein the first image and the second image have the same size and are the same except for transparent areas. A second mask bitmap is created which displaces pixels of first RGB values in the first image to second RGB values. The first mask bitmap is applied to the second mask bitmap by performing an ‘OR’ operation on the first and second mask bitmaps. Pixels in the resulting bitmap of the ‘OR’ operation which have the first RGB values are transparent. Pixels in the resulting bitmap of the ‘OR’ operation, corresponding to the pixels in the first image that had the first RGB values, have the second RGB values. Pixels are identified in the resulting bitmap of said ‘OR’ operation which have said first RGB values as transparent.
The process according to the invention comprises the steps of:
Step 1: Create a First Mask Bitmap to Define the Transparent Areas
This step starts by combining two images (Image 1 and Image 2) with different background colors using an ‘exclusive or’ operation.
These two images have the same size and are the same except for transparent areas. Table 1 shows the key referring to positions of 9 pixels in the bitmap for the images. In image 1, all areas where should be transparent are set to black (0, 0, 0) as shown in Table 2. In image 2, all areas where should be transparent are set to white (255, 255, 255) as shown in Table 3.
The ‘exclusive or’ operation on these two images creates two binary results for each position: it is 1 if two values in a same position are different, and it is 0 if two values in a same position are same.
Referring to Table 4, after the ‘exclusive or’ operation is performed, the resulting rgb values at positions (2,1), (3,1) and (3,2) are set to white (255, 255, 255) because the corresponding bits in each of these positions were different. All other areas are set to black (0, 0, 0) because the corresponding values in two images were equal.
Then, subtract 1 from the bitmap shown in Table 4. After the ‘subtraction’ operation, all black pixels (0,0,0) remains unchanged, and all white pixels (255, 255, 255) are changed to quasi-white (254, 254, 254). These pixels with rgb values (254, 254, 254) at positions (2,1), (3, 1) and (3,2) are transparent areas. The bitmap shown in Table 5 is hereby named as the first mask bitmap.
Step 2: Change Pixels in the Original Bitmap that Had RGB Values (254, 254, 254) to Pixels with RGB Values (255, 255, 255)
Two sub-steps are used to change any pixels that were originally quasi white (254, 254, 254) to white (255, 255, 255), so that transparency is not shown where it should not be shown. This is an operation on the original bitmap of Image 1, which had black pixels where the transparent areas should be shown. There may be other black pixels that can be handled by this algorithm.
Step 2A: Create a Second Mask Bitmap
This sub-step comprises:
Comparing Table 2 with Table 9, it is clear that any pixels that were originally quasi-white (254, 254, 254) in Image 1 (Table 2) are now white (255, 255, 255) in the mask bitmap (Table 9) and all other pixels in Image 1 (Table 2) are now black (0, 0, 0) in the mask bitmap (Table 9).
Step 2B: Apply the Second Mask Bitmap to the Original Bitmap
This is to apply the second mask bitmap (Table 9) from Step 2A to the original bitmap (Table 2) using an ‘or’ operation, wherein 0 or'd with anything returns the original value, and 255 (binary 11111111) or'd with anything returns 255.
After the ‘or’ operation, any pixels that were quasi-white (254, 254, 254) in Table 2 now become white (255, 255, 255) and all other pixels in Table 2 keep unchanged as shown in Table 10. In this operation, actually any pixels that had a byte with a value of 254 in Table 2 now is changed to a byte with a value of 255, which is almost indistinguishable in the exported image.
Step 3: Apply First Mask Bitmap to Second Mask Bitmap
This is to apply the first mask bitmap from Step 1 shown in Table 5 to the second mask bitmap from Step 2B shown in Table 10 using an ‘or’ operation, wherein 0 or'd with anything returns the original value, and 255 (binary 11111111) or'd with anything returns 255.
The result of the ‘or’ operation is the bitmap where the set of pixels with rgb values (254, 254, 254) should be transparent. The transparent file is written out with that color marked as the transparent color. Any pixels that originally had rgb values (254, 254, 254) now have rgb values (255, 255, 255), a change that is very close to the original and not visible to most users.
Table 11 shows the expected result from applying the process to the two input bitmaps. The rgb values of the positions (1,2), (2,2), (1,3) and (2,3) in the exported image are unchanged from their original values. The position at (3,3) has changed from rgb values (254, 254, 254) to rgb values (255, 255, 255). This is desired because the image is to be saved for displaying all pixels with rgb values (254, 254, 254) as transparent and the pixel at the position (3,3) should not be transparent. The pixels at (2,1), (3,1) and (3,2) all have rgb values (254, 254, 254), which are treated as transparent.
Table 12 is the VBScript code implementation of the process described herein.
In the process described herein, the value 254 is preferably used for the first mask bitmap i.e. the bitmap after ‘subtraction’ and the first temporary bitmap. In actuality, any eight-bit value close to white, such as 253 or 252, may be used. The problem is that, in the final step, the pixels of that value need to be displaced to the value of 255 and the further that value is from 255, the more noticeable the difference will be.
This invention is preferably used in a system where the input images does not encode transparency directly, but rather outputs transparent pixels in a color that is specified. In addition, the output images need to be set in a format e.g. GIF, PNG, which assigns transparency to pixels based on their color. Finally, this invention is optimized for situations where wholesale bitmap operations are faster than manipulating each byte individually. For instance, the MMX capability of recent Pentium chips (Intel Corporation, Santa Clara, Calif.) has this optimization.
Although the invention is described herein with reference to the preferred embodiment, one skilled in the art will readily appreciate that other applications may be substituted for those set forth herein without departing from the spirit and scope of the invention.
Accordingly, the invention should only be limited by the claims included below.
This application is a 371 of PCT/US01/03171 Jan. 31, 2001, which claims benefit of 60/180,440 Feb. 4, 2000.
Filing Document | Filing Date | Country | Kind | 371c Date |
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PCT/US01/03171 | 1/31/2001 | WO | 00 | 8/2/2002 |
Publishing Document | Publishing Date | Country | Kind |
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WO01/57800 | 8/9/2001 | WO | A |
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