You have to decide what is "similar." Contrast? Hue?
Is a picture "similar" to the same picture upside-down?
I bet you can find a lot of "close calls" by breaking images up into 4x4 pieces and getting an average color for each grid cell. You'd have sixteen scores per image. To judge similarity, you would just do a sum of squares of differences between images.
I don't think a single hash makes sense, unless it's against a single concept like hue, or brightness, or contrast.
Here's your idea:
0299393
0599483
0499994 <- possible dupe
0499999 <- possible dupe
1002039
4995994
6004994
First of all, I'm going to assume these are decimal numbers that are R*(2^16)+G*(2^8)+B, or something like that. Obviously that's no good because red is weighted inordinately.
Moving into HSV space would be better. You could spread the bits of HSV out into the hash, or you could just settle H or S or V individually, or you could have three hashes per image.
One more thing. If you do weight R, G, and B. Weight green highest, then red, then blue to match human visual sensitivity.