A Novel Approach for Image Segmentation based on Histograms computed from Hue-data
This work addresses a specific problem in computer vision for applications like object recognition in controlled backgrounds, but it appears incremental as it builds on existing histogram-based methods.
The paper tackles image segmentation for images with uniformly colored backgrounds, such as flowers or birds, by proposing a novel algorithm based on histograms computed from hue-data, aiming to enhance computer visualization and achieve near-human accuracy in classification.
Computer Vision is growing day by day in terms of user specific applications. The first step of any such application is segmenting an image. In this paper, we propose a novel and grass-root level image segmentation algorithm for cases in which the background has uniform color distribution. This algorithm can be used for images of flowers, birds, insects and many more where such background conditions occur. By image segmentation, the visualization of a computer increases manifolds and it can even attain near-human accuracy during classification.