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Both approaches can work, among many others certainly. I see exactly where you decided to focus on lines continuity. Yet I've opted for something which is more like a "rotozoomer", and based on textures processing. I've started implementing it to see how it works. http://www.beyondwonderland.com/data/java/barcodes/header.html [url=http://www.beyondwonderland.com/data/java/barcodes/gfx/gfx.zip]source code[/url] At this stage, I have: - left and right edge pixels (red) - extremums (top left, right, bottom left, right)(blue) From this, I can use my extremums to determine which point in the edge pixels is the closest, and therefore spot my ABCD points in the above piccis (really catch the barcode "tile"). If I had many barcodes, and I will test that too, I'd make a first "identification" pass based on uniformity of colors. for example: subdivide the picture using a grid, compute the color uniformity of an area, if it's uniform give it up, otherwise label it workable. Subdivide the remaining squares in smaller squares and repeat, until you get to quite small squares. Treat remaining "groups" of pixels by copying them to new images, which will pass through the "vectorizer". In the vectorizer part of the code, check only two three lines of the "supposed" barcode, if you find they describe the same barcode, then chances are... It is right. For circles, as you said, work from the center along the radius. [quote] Note to self: this could be developed further to recognize the 3d perspective of an image with two three barcodes, and probably start 3d reconstruction... [/quote] [img]http://www.beyondwonderland.com/data/images/sigs/devil2.gif[/img]
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