What is Image Comparison?

Image comparison is a method that is used to detect the differences between two different or probably similar pictures. This method is based on different factors like spatial resolution, image quality, contrast, noise, etc. Image comparison techniques are widely used in the medical field, social media, AI field, etc.

What is Image Comparison?

Image comparison is the process of analyzing and comparing two or more images to determine their similarities, differences, or changes. This technique is used in various fields like computer vision, digital forensics, medical imaging, and photography.

Image Comparison Techniques

• Pixel tolerance : In this technique, find the maximum number of dissimilar pixels between two apparently similar pictures.

If (number of dissimilar pixels <= pixel tolerance) then pictures are identical

• SIFT algorithm: It stands for Scale-Invariant Fourier Transform. This algorithm is used to extract distinct ( something else of the same type ) key points from an image and using these key points identify the differences between the lightly same pictures. That's why this technique is also known as the Key Detection Comparison technique.
• SSIM: stands for Structural similarity index measure. This technique is based on perception. In this technique, focuses on the perceptual difference between two apparently similar pictures.
• PSNR :It stands for Peak-Signal-To-Noise-Ratio. In this technique, notice the high numerical difference between two similar pictures.
• Histogram comparison : This technique is very simple and easy. This technique is focuses on pixels and color. It means, check pixels with same color is same in between two pictures then both pictures are similar.

Comparison Engine Parameters

Comparison Engine Parameters are a group of parameters which are used to generate the similarity scoring so that identify the similar images. Some parameters are -

• Pixel Tolerance - Find the maximum number of dissimilar pixels between two apparently similar pictures. If (number of dissimilar pixels <= pixel tolerance) then pictures are identical
• Color Tolerance - Color is represented by integer value within the range 0 to 255 and using this value find the pixels color. If color tolerance is Zero then image is identical.
• Transparent Color - Pixels that have transparent color act as a coordinate so that not compare all the pixels.
• Comparison Mask - Comparison mask is a image, which has only black and white pixels. Black pixels are excluded from comparison.

Factors Affecting Comparison

Some factors that can affect image comparison:

• Spatial resolution : Spatial resolution also known as pixel size and measure of the distance between dimension of pixel in a image.
• Image quality : All the Image Comparison techniques generate the result easier if image has good quality because extraction of information from a good quality of a image is very easy.
• Noise : Noise means unwanted signals which is affect on image detail. Removing the noise on image is very challenging.
• Brightness : Brightness is affect indirectly. They affect image quality and colors. Because of many Image Comparison technique based on image quality and colors of pixels.
• Contrast : It define the difference in brightness between light and dark areas. That's why this is an important factor.
• Image size : Some pictures has same height and width. But if size is different then pictures are unequal.
• Color depth : Two pictures has same icon or any things but with different shades or color. So these types of pictures are unequal.

Advantages of Image Comparison

• Accuracy : Image Comparison algorithms can detect differences between same or different images. But by human eye, can not detect result.
• Medical Diagnostics : Using image comparison, doctors can easily find the diseases (like in X-ray or any medical scans).
• Environmental Monitoring : Human can not detect changes in land ( like deforestation ). That's way click the photo over time by using satellite and using image comparison identify the changes.
• Facial Recognition : Image comparison algorithm is main component in facial recognition system. Using image comparison, check face is match with saved data in database or not.
• Training AI models : Image comparison helps to create the training datasets for AI models.
• Photo Organization : Easily categorized and organized images collections with the help of image comparison.

Disadvantages of Image Comparison

• High Computational Requirements.
• Implementation is very complex.
• There is a chance that it could be misused.

Conclusion

At present, Image comparison techniques are widely used. For example Google Photo, This is a product of Google and store the photo. It provide a feature, in which photos are automatically categorized based on face by using Image comparison techniques. All we know, now are the store big data ( large amount of data) and work on. So their is very difficult to get summary in some cases. To reduce this trouble use image comparison to find and get the expected result. Image comparison will be more improved in upcoming future because It is very helpful for AI training.

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Article Tags :

• Electronics Engineering
• Digital Image Processing