Published Paper Details:

Evolution of data communications in the early days was mainly numerical and textual form. Many other forms of data: voice, music, speech, images, computer graphics, etc as specified mostly in the form of electrical or electronic signals. A Signal is a function that conveys information. The concept of digital image processing was introduced relatively late in computer history after the arrival of the first graphical operating systems. More ever, digital image processing requires the most careful optimizations especially for real time applications. Transfer of the messages as signals through electronic media: telegraphs, telephones, television, radar, etc. may be affected by the systems used to acquire, transmit, or process them. Also these systems are imperfect and introduce noise, distortion, or other artifacts leading to necessity of the signal processing. Accordingly, we specifically introduce the information content into the signal to extract it out later by encoding natural phenomena (audio signal, acquired image, etc.), but also generated from scratch (speech generation, computer generated music, computer graphics). Ofllate these technologies are merged together by acquiring a natural signal, processing it, and then transmitting it in some electronic form. This form is called Digital Image Processing. Computer vision aims to duplicate the effect of human vision by electronically perceiving and understanding an image. Incurring an enormous loss of information in due processing. In order to simplify the task of computer vision processing, two levels are usually distinguished viz: Low-level image processing and High-level image processing. Low level images processing methods usually use very little knowledge about the content of image. In the case of the later, it is usually provided by high-level algorithms. Low level methods often include image compression, pre-processing methods for noise filtering, edge extraction, image sharpening and boundary detection for image classification and analysis. High-level image processing is based on knowledge, goals, and plans of how to achieve those goals, and artificial intelligence methods are widely applicable. In this thesis low level image processing methods have been studied for image segmentation and classification of images.