Leadtools OCR

This project benchmarks and compares the performance and accuracy of two leading OCR (Optical Character Recognition) engines: Aspose.OCR and Leadtools.OCR. The goal is to evaluate their effectiveness on a real-world dataset and provide clear, quantitative results for both speed and recognition quality.

This benchmark uses:

  • Aspose.OCR for .NET 25.7.0 (release date: 14.07.2025)
  • Leadtools.Ocr 23.0.0.4 (release date: 02.01.2025)

Licensing Requirements

Both Aspose.OCR and Leadtools.OCR are commercial products and require valid licenses to operate in full-feature mode.

  • Aspose.OCR: Requires a valid license file (e.g., Aspose.OCR.NET2025_2.lic).
  • Leadtools.OCR: Requires a valid license and key file (e.g., LEADTOOLS.lic and LEADTOOLS.lic.key).

    Licenses must be properly installed and referenced in the application for the engines to function without limitations or watermarks.

Dataset

  • The benchmark was conducted on a dataset containing 994 images .
  • Each image has a corresponding ground-truth text file for accuracy evaluation.

Benchmark Results



Engine
Average Time per Image   
Levenshtein Error (%)
Aspose
2.25 seconds
3.27%
Aspose (using AI Spell-check)   
62.3 seconds
3.15%
Leadtools
0.99 seconds
5.13%


  • Time per Image: Average time taken to process a single image.
  • Levenshtein Error (%): Average percentage difference between the recognized text and the ground-truth, measured using the Levenshtein distance (lower is better).

Interpretation

  • Aspose.OCR provides slightly better recognition accuracy (lower Levenshtein error), but is slower.
  • Leadtools.OCR is significantly faster, with a small trade-off in recognition accuracy.

Example 1

Original Image 3717 symbols

OCR Example

Aspose OCR vs Aspose OCR AI

OCR 0.43% errorsOCR + LLM 0.27% errors

Aspose OCR Example

Aspose OCR Example

Leadtools OCR

0.7% errors

Leadtools OCR Example

Key Differences and Analysis

Type of DifferenceAsposeAspose (AI)LeadtoolsEthalon
Punctuation
ll7(c)
117(c)
ll7(c), 60 days ,
117(c)
Case Sensitivity
C&c, DoE, c&c
C&c
the DOE, C8
C&C, DOE
Character Substitution
none significant
none significant
VolLl.l'lll€ I, C86, C8
n/a
Word Substitution
none
none
C86 agreements
n/a
Missing Content
none
none
none
complete



Example 2

Original Image 968 symbols

OCR Example

Aspose OCR vs Aspose OCR AI

OCR 3.51% errorsOCR + LLM 2.79% errors

Aspose OCR Example

Aspose OCR Example

Leadtools OCR

65.5% errors

Leadtools OCR Example

Key Differences and Analysis

Type of Difference

Aspose

Aspose (AI)

Leadtools

Ethalon

Punctuation
August 19. 1993
It'"", please cati us
August 19. 1993
It'""
lots of garbled punctuation  
August 19, 1993
It's, please call us
Case Sensitivity
sincerely, AsMc
illinois
sincerely, AsMc
illinois
Random casing and symbols
Sincerely, ABMC, Illinois
Character Substitution
Il, Medica1, We'17
Il
ALE>q/\N, MP. Rica 4 
Gm he rGad...
IL, Medical, We'll
Word Substitution
Fer_more, cati us
None
Heavy distortion
For more, call us
Missing Content
None
None
Meaning lost due to garbling
None



  • Aspose: Very close to the ethalon, with only minor punctuation and case errors. No missing content.
  • Leadtools: Slightly less accurate, with a typo (“t1ons”), a word substitution (“systan operation”), and more case inconsistencies.

    Aspose is more reliable for this sample, as reflected in the lower Levenshtein error (0.83% vs 1.7%).

Easy to use Aspose.OCR API

Aspose OCR API simplifies text extraction by handling image analysis and processing automatically, letting users focus on their core tasks—just provide an image and and leave the rest to the API.

Convert image to text

/** Initialize recognition API */
AsposeOcr api = new AsposeOcr();

/** Provide the image for recognition */
OcrInput source = new OcrInput(InputType.SingleImage);
source.Add("image.png");

/** Recognize and output results */
List<RecognitionResult> results = api.Recognize(source);
Console.WriteLine(results[0].RecognitionText);
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