![]() ![]() Image smoothing ameliorates the effect of high-frequency spatial noise from an image. Upskill yourself for your dream job with industry-level big data projects with source code 2) Image Smoothing Alternatively, you could attempt to implement other Grayscaling algorithms like the Lightness and the Average Method. The results look similar to the Grayscale image in the figure with minor variations in contrast because of the difference in the formula used. For this project, you are advised to use the Luminosity Method, which uses the formula 0.21*R+0.72*G+0.07*B. For this image processing project, you could import the color image of your choice using the Pillow library and then transform the array using NumPy. There are plenty of readily available functions in OpenCV, MATLAB, and other popular image processing tools to implement a grayscaling algorithm. (Image used from Image Processing Kaggle) ![]() The output image shown above has been grayscaled using the rgb2gray function from scikit-image. This process is almost indispensable even for more complex algorithms like Optical Character Recognition, around which companies like Microsoft have built and deployed entire products (i.e., Microsoft OCR). Grayscaling is among the most commonly used preprocessing techniques as it allows for dimensionality reduction and reduces computational complexity. You will find this section most helpful if you are a student looking for image processing projects for the final year. This section has easy image processing projects ideas for novices in Image processing. Predictive Analytics Project for Working Capital Optimization View Project Since one of the best ways to get an intuitive understanding of the field can be to deconstruct and implement these commonly used functions yourself, the list of image processing projects ideas presented in this section seeks to do just that! ![]() As if to make matters worse for a beginner, the myriad of high-level functions implemented can make it extremely hard to navigate. With the vast expectations the domain bears on its shoulders, getting started with Image Processing can unsurprisingly be a little intimidating.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |