匹配图像到图像集合 [英] Matching image to images collection

问题描述

我有大量的卡片图片和一张特定卡片的照片。我可以使用哪些工具来查找哪些图像与我的图像最相似？

I have large collecton of card images, and one photo of particular card. What tools can I use to find which image of collection is most similar to mine?

这是集合示例：

• Abundance


• < a href =http://i.imgur.com/o7dwAoq.jpg =nofollow>激进的敦促


• 揭秘

• Abundance
• Aggressive Urge
• Demystify

这就是我正在尝试的找到：

Here's what I'm trying to find:

• 卡照片

• Card Photo

推荐答案

感谢您发布一些照片。

我编写了一个名为 Perceptual Hashing 的算法，我是Neal Krawetz博士发现的。在将您的图像与卡片进行比较时，我得到以下百分比相似度：

I have coded an algorithm called Perceptual Hashing which I found by Dr Neal Krawetz. On comparing your images with the Card, I get the following percentage measures of similarity:

Card vs. Abundance 79%
Card vs. Aggressive 83%
Card vs. Demystify 85%

因此，它是不是你的图像类型的理想鉴别器，但有点工作。您可能希望使用它来为您的用例量身定制。

so, it is not an ideal discriminator for your image type, but kind of works somewhat. You may wish to play around with it to tailor it for your use case.

我会为您的集合中的每个图像计算一个哈希值，一次一个只存储一次每个图像的哈希值。然后，当你得到一张新卡时，计算它的哈希并将其与存储的卡进行比较。

I would calculate a hash for each of the images in your collection, one at a time and store the hash for each image just once. Then, when you get a new card, calculate its hash and compare it to the stored ones.

#!/bin/bash
################################################################################
# Similarity
# Mark Setchell
#
# Calculate percentage similarity of two images using Perceptual Hashing
# See article by Dr Neal Krawetz entitled "Looks Like It" - www.hackerfactor.com
#
# Method:
# 1) Resize image to black and white 8x8 pixel square regardless
# 2) Calculate mean brightness of those 64 pixels
# 3) For each pixel, store "1" if pixel>mean else store "0" if less than mean
# 4) Convert resulting 64bit string of 1's and 0's, 16 hex digit "Perceptual Hash"
#
# If finding difference between Perceptual Hashes, simply total up number of bits
# that differ between the two strings - this is the Hamming distance.
#
# Requires ImageMagick - www.imagemagick.org
#
# Usage:
#
# Similarity image|imageHash [image|imageHash]
# If you pass one image filename, it will tell you the Perceptual hash as a 16
# character hex string that you may want to store in an alternate stream or as
# an attribute or tag in filesystems that support such things. Do this in order
# to just calculate the hash once for each image.
#
# If you pass in two images, or two hashes, or an image and a hash, it will try
# to compare them and give a percentage similarity between them.
################################################################################
function PerceptualHash(){

   TEMP="tmp$$.png"

   # Force image to 8x8 pixels and greyscale
   convert "$1" -colorspace gray -quality 80 -resize 8x8! PNG8:"$TEMP"

   # Calculate mean brightness and correct to range 0..255
   MEAN=$(convert "$TEMP" -format "%[fx:int(mean*255)]" info:)

   # Now extract all 64 pixels and build string containing "1" where pixel > mean else "0"
   hash=""
   for i in {0..7}; do
      for j in {0..7}; do
         pixel=$(convert "${TEMP}"[1x1+${i}+${j}] -colorspace gray text: | grep -Eo "\(\d+," | tr -d '(,' )
         bit="0"
         [ $pixel -gt $MEAN ] && bit="1"
         hash="$hash$bit"
      done
   done
   hex=$(echo "obase=16;ibase=2;$hash" | bc)
   printf "%016s\n" $hex
   #rm "$TEMP" > /dev/null 2>&1
}

function HammingDistance(){
   # Convert input hex strings to upper case like bc requires
   STR1=$(tr '[a-z]' '[A-Z]' <<< $1)
   STR2=$(tr '[a-z]' '[A-Z]' <<< $2)

   # Convert hex to binary and zero left pad to 64 binary digits
   STR1=$(printf "%064s" $(echo "obase=2;ibase=16;$STR1" | bc))
   STR2=$(printf "%064s" $(echo "obase=2;ibase=16;$STR2" | bc))

   # Calculate Hamming distance between two strings, each differing bit adds 1
   hamming=0
   for i in {0..63};do
      a=${STR1:i:1}
      b=${STR2:i:1}
      [ $a != $b ] && ((hamming++))
   done

   # Hamming distance is in range 0..64 and small means more similar
   # We want percentage similarity, so we do a little maths
   similarity=$((100-(hamming*100/64)))
   echo $similarity
}

function Usage(){
   echo "Usage: Similarity image|imageHash [image|imageHash]" >&2
   exit 1
}

################################################################################
# Main
################################################################################
if [ $# -eq 1 ]; then
   # Expecting a single image file for which to generate hash
   if [ ! -f "$1" ]; then
      echo "ERROR: File $1 does not exist" >&2
      exit 1
   fi
   PerceptualHash "$1" 
   exit 0
fi

if [ $# -eq 2 ]; then
   # Expecting 2 things, i.e. 2 image files, 2 hashes or one of each
   if [ -f "$1" ]; then
      hash1=$(PerceptualHash "$1")
   else
      hash1=$1
   fi
   if [ -f "$2" ]; then
      hash2=$(PerceptualHash "$2")
   else
      hash2=$2
   fi
   HammingDistance $hash1 $hash2
   exit 0
fi

Usage

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