Main Article Content
Image analysis involves investigation of the image data for a specific application. Normally, the raw data of a set of images is analyzed to gain insight into what is happening with the images and how they can be used to extract desired information. In image processing and pattern recognition, feature extraction is an important step, which is a special form of dimensionality reduction. When the input data is too large to be processed and suspected to be redundant then the data is transformed into a reduced set of feature representations. The process of transforming the input data into a set of features is called feature extraction. Features often contain information relative to color, shape, texture or context. In the proposed method various texture features extraction techniques like GLCM, HARALICK and TAMURA and color feature extraction techniques COLOR HISTOGRAM, COLOR MOMENTS AND COLOR AUTO-CORRELOGRAMare implemented for tiles images used for various defects classifications.
How to Cite
, C. U. D. R. B. D. K. . (2018). Texture and Color Feature Extraction Form Ceramic Tiles for Various Flaws Detection Classification. International Journal on Future Revolution in Computer Science &Amp; Communication Engineering, 4(1), 169–179. Retrieved from https://ijfrcsce.org/index.php/ijfrcsce/article/view/986