{
  "id": "1707.09643",
  "version": "v1",
  "published": "2017-07-30T17:23:56.000Z",
  "updated": "2017-07-30T17:23:56.000Z",
  "title": "A Novel Approach for Image Segmentation based on Histograms computed from Hue-data",
  "authors": [
    "Viraj Mavani",
    "Ayesha Gurnani",
    "Jhanvi Shah"
  ],
  "comment": "4 pages",
  "journal": "International Journal for Scientific Research and Development [Conference 10 : NCACSET 2017] (2017): pg. 176-179",
  "categories": [
    "cs.CV"
  ],
  "abstract": "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.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2017-07-30T17:23:56.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "novel approach",
      "grass-root level image segmentation algorithm",
      "histograms",
      "uniform color distribution",
      "attain near-human accuracy"
    ],
    "tags": [
      "journal article"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 4,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}