Image analysis enables to get meaningful information from a digital image by applying the image processing techniques. During the process of extracting of this meaningful information number of challenges needs to be addressed for a high-resolution image. These high-resolution images which contain minimum of 300 pixels per inch are also known as ‘coarse’ images. One common problem of coarse image is it combines the spectral properties of intermixed pixels. This nature of coarse image will lead to ambiguity in grouping the pixels into clusters which are in turn constitute to different objects in the input image. To reduce this ambiguity in classifying or grouping the pixels, Ant Colony Optimization and Fuzzy Logic which is a Hybrid classification technique is proposed. The ACO has solved many classification problems. In this paper ACO and Fuzzy based to group the pixels into meaningful groups for coarse image and results are compared with various other unsupervised classification methods such as ISODATA and K-means

Image analysis is the process of extracting quantitative and useful content from images by means of image processing approaches. In Image analysis, the classification process plays vital role in arranging the pixels into groups, called clusters that are similar in characteristics. In this paper a novel hybrid image classification method is proposed, which is used to analyze both textured and non-textured images. The image classification generally makes an attempt to group all the pixels that are strongly related to the objects in the image of interest. Classification rules are extracted from the input image using the unsupervised swarm intelligence technique called ant colony optimization (ACO), which are then used to group pixels. These classification rules are obtained from the training set of the image and further pruning process is applied to eliminate those rules that contribute less in the classification process on the test set of the image. Fuzzy partitioning technique along with ACO is used to generate simple rules to produce better results.