An adaptive machine learning algorithm for color image analysis and processing

✍ Scribed by Mehmet Celenk

• Publisher: Elsevier Science
• Year: 1988
• Tongue: English
• Weight: 522 KB
• Volume: 4
• Category: Article
• ISSN: 0736-5845
• DOI: 10.1016/0736-5845(88)90011-7

✦ Synopsis

In this paper, a new adaptive machine learning algorithm for analyzing and processing color images of natural scenes is presented . The eventual goal of this research is to obtain a mathematical training algorithm to guide the operation of an unsupervised pattern recognition and classification technique for detecting and extracting the image modes or clusters in a selected or constructed feature space . For this purpose, the peak modality of one-dimensional (1-D) image histograms is selected as the mathematical training criterion . Area, mode dispersion, approximated curvature and steepness are some of the measured quantities for a modality test . Linear discriminant function is then used to extract the detected image dusters in the feature or measurement space.