Find Similar Pictures

This search method enables you to find similar or almost identical pictures. For each image will be a checksum calculated for further comparison with all other images.

Comparison Method
Hints
Image Formats
Percentage Match
Picture Area
Compare Size
Checksum
Compare only pictures with the same properties
Detect picture modifications (slower)
Recognition Rate Test
Examples

Comparison Method

The comparison methods aHash, bHash, dHash and pHash enables you to find similar or almost identical pictures by using a percent match lower than 100%. If you want find exactly the same pictures you have to use a percent match of 100% or the comparison methods MD5/SHA. An overview of the recognition rate of the comparison methods aHash, bHash, dHash and pHash can be found here.

aHash
The comparison method aHash (Average Hash) resizes the image to 8x8 or 16x16 pixel. The image will be converted to grayscale and the average color of the all image pixel will be calculated. Now the checksum will be created based on whether the pixel's value is greater than the average color of the image. The checksum can be 64-bit (8x8 pixel) or 256-bit (16x16 pixel).
bHash
The comparison method bHash (Blockhash) resizes the image to 128x128, 256x256 or 512x512 pixel. The image will be divided into a block matrix and the median value of all blocks will be calculated to create the checksum. The checksum can be 64-bit or 256-bit. The options "Fast" and "Precise" enables you to influence the accuracy of the checksum calculation.
dHash
The comparison method dHash (Difference Hash) resizes the image to 8x8 or 16x16 pixel. The image will be converted to grayscale and the relative change in brightness intensity between two pixels will be calculated to create the checksum. The checksum can be 64-bit (8x8 pixel) or 256-bit (16x16 pixel).
pHash
The comparison method pHash (Perceptual Hash) resizes the image to 32x32 pixel. The image will be converted to grayscale and the 64-bit checksum will be calculated based on the frequency spectrum data and a distance calculation doing a discrete cosine transform (DCT).
MD5, SHA
These comparison methods enables you to find exactly the same pictures. The following comparison methods are available:
- MD5 (128-Bit)
- SHA-1 (160-Bit)
- SHA-2 (256-Bit)
- SHA-2 (384-Bit)
- SHA-2 (512-Bit)

For more information on the aHash, bHash, dHash, and pHash comparison methods, see articles Testing different image hash functions and Detection of Duplicate Images Using Image Hash Functions.

Hints

The following files will be automatically excluded from the search:

Files with a size of 0 bytes
Pictures with a width or height smaller than the specified compare size
Corrupted, invalid or incomplete pictures (*)
Files with a blocked read access (*)

(*) An error message will be shown at the log pane.

Image Formats

Here you can specify which image formats should be checked during a search. Image files with the following file extensions are supported: 3FR, ARW, BMP, CR2, CRW, CUT, DCR, DIB, DNG, EMF, ERF, GIF, HDP, ICO, IFF, J2C, J2K, JP2, JPE, JPG, JPEG, JPX, JFIF, KDC, MDC, MEF, MOS, MRW, NEF, ORF, PEF, PBM, PCX, PGM, PNG, PPM, PSD, RAF, RAS, RAW, RW2, SRW, TGA, TIF, TIFF, RAS, RLE, WBMP, WEBP, WMF and X3F.

Percentage Match

Here you can specify the minimum percentage matching of two pictures. The calculated percentage matching between two pictures will be shown at the column Match. The percentage always refers to the reference picture of a group which will be shown in a different text color.

Picture Area

This option enables you to specify the picture area to be used to create the checksum. The following options are available:

entire picture
area at the upper left corner
area at the upper right corner
area at the lower left corner
area at the lower right corner

When using the options 2, 3, 4 or 5, the size of the picture area can be specified in pixel. For example, a value of 16 pixel will be using a picture area with a width and height of 16 pixel at the selected corner.

Compare Size

Here you can specify the maximum width and height of the pictures to be compared. A lower compare size finds more similar pictures and speeds up the comparison time. A higher compare size finds more identical pictures and less similar pictures and of course needs more time to compare them.

Checksum

The size of the checksum in bits is displayed here. The checksum can only be changed when using the bHash comparison method.

Compare only pictures with the same properties

This option will be performed before the option Detect picture modifications.

File Name
This option enables you to compare only pictures with the same file name.
File Extension
This option enables you to compare only pictures with the same file extension.
Width and Height
This option enables you to compare only pictures with the same width and height.
Orientation
This option enables you to compare only pictures with the same orientation (portrait or landscape).
Aspect Ratio
This option enables you to compare only pictures with the same aspect ratio. The calculation of the aspect ratio is done by the formula "width divided by height". The result of the calculation is truncated to one decimal place. A picture with 1920x1080 pixel has an aspect ratio of "1.7".

Detect picture modifications (slower)

This option enables you to detect different picture modifications when comparing two pictures. For this purpose, each picture modification will be performed with the picture to be compared and in each case an additional checksum will be created. The following picture modifications can be detected:

Rotated 90° to the right
Rotated 180° to the right
Rotated 90° to the left
Flipped horizontally
Rotated 90° to the right and flipped horizontally
Flipped vertically
Rotated 90° to the left and flipped horizontally

Recognition Rate Test

We have carried out tests with various comparison methods to determine the recognition rate for different image changes. For this purpose, 29 copies of a JPEG image (1600x1200px, 606KB) were created and their color, size and format changed. The tests always compared the original JPEG image and a modified copy of the image.
The following comparison methods were used in the test:

aHash, compare size: 16x16, checksum: 256-bit
bHash (fast), compare size: 256x256, checksum: 256-bit
dHash, compare size: 16x16, checksum: 256-bit
pHash, compare size: 32x32, checksum: 64-bit

The percentage values in the table show how well a comparison method recognizes the change in the image copy:

Image Modification	aHash	bHash	dHash	pHash
Image reduction to 75%	100%	100%	100%	97%
Image reduction to 50%	100%	100%	99%	100%
Image reduction to 25%	100%	100%	99%	97%
Image enlargement to 150%	100%	100%	100%	100%
Image enlargement to 200%	100%	100%	100%	100%
Conversion to grayscale	98%	97%	97%	97%
Brightness increased by 30%	99%	100%	98%	91%
Brightness decreased by 30%	95%	89%	92%	91%
Contrast increased by 30%	99%	95%	96%	94%
Contrast decreased by 30%	99%	100%	98%	94%
JPEG quality reduced by 25%	100%	100%	100%	100%
JPEG quality reduced by 50%	100%	100%	99%	100%
JPEG quality reduced by 75%	100%	100%	99%	94%
Image rotated 90° to the left	52%	68%	46%	47%
Image rotated 90° to the right	52%	54%	48%	44%
Image flipped vertically	81%	77%	71%	50%
Image flipped horizontally	59%	62%	54%	47%
Added white frame (30px)	82%	68%	86%	88%
Added black frame (30px)	94%	92%	92%	88%
Image height reduced to 80%	100%	100%	100%	100%
Image width reduced to 80%	100%	100%	99%	100%
Conversion to PNG 24bit	100%	100%	100%	100%
Conversion to BMP 24bit	100%	100%	100%	100%
Conversion to GIF 256 colors	100%	100%	99%	97%
Cropped 100 pixel from the left edge	91%	88%	82%	78%
Cropped 100 pixel from the right edge	92%	86%	85%	91%
Cropped 100 pixel from the top edge	88%	86%	86%	84%
Cropped 100 pixel from the bottom edge	91%	87%	86%	84%
Cropped 100 pixel from all edges	80%	77%	70%	62%

The following table gives you an overview of how many duplicates were found with the various comparison methods in the test. The evaluation was carried out with a Percentage Match of at least 70%, 80% and 90%.