World of Computer Science and Information Technology Journal (WCSIT) ISSN: 2221-0741 Vol. 1, No. 9, 370-375, 2011 370 A Hybrid Method for Enhancement of Plant Leaf Recognition N.Valliammal Assistant Professor, Department of Computer Science, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore-641 043. INDIA Dr.S.N.Geethalakshmi Associate Professor, Department of Computer Science, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore-641 043. INDIA Abstract— This paper focuses on the preprocessing technique for CAP-LR (Computer aided plant classification through leaf recognition). Pre-processing is the basic step to reconstruct the image with some useful feature. This technique is essential for the enhancement of leaf images which increases the efficiency of the subsequent tasks of the leaf recognition system. In this paper, an hybrid approach is proposed which is a combination of contrast stretching and adaptive thresholding that simultaneously adjusts the intensity level of leaf images using boundaries is developed. The validation of proposed system is carried out based on the defined parameter matrices. The experimental results shows that the proposed method proves efficient when compared to other traditional methods. Keywords- image enhancement; Histogram equalization; Contrast stretching; intensity adjustment; Adaptive Thresholding; Median filter; wavelet filter. I. INTRODUCTION The application of digital image processing techniques for the problem of automatic leaf classification began two decades ago and it has since been proceeding in earnest. In industrial agriculture this technology found some of its earlier applications to be widely used. Image sequence processing techniques are used to solve problems in environmental biology. Plant is important for environment protection. However, the problem of plant destruction becomes worse in recent years. Hence many types of plants are at the risk of extinction. To protect plants and to catalogue various types, construction of automatic plant recognition system is an important step towards conservation of earth’s biosphere. There are several ways to recognize a plant like flower, root, leaf, fruit etc. In recent times computer vision methodologies and pattern recognition techniques have been applied towards automated procedures of plant recognition [2,3]. Plant leaves are approximately two-dimensional in nature and the shape of plant leaf is one of the most important features for characterizing various plants species. It helps in the development of an automatic method that can correctly discriminate and recognize leaf shapes of different species. These applications require high accuracy for the estimation of dynamic changes. Automatic classification and recognition system for plant is essential and useful since it can facilitate fast learning of plants [4,7]. Leaf images normally changes to blurred images by the presence of noise, low or high contrast both in the edge area and image area. Preprocessing an image include, removal of noise, edge or boundary enhancement, automatic edge detection, automatic contrast adjustment and segmentation. As multiple noise damages the quality of nature images, improved enhancement technique is required for improving the contrast stretch in leaf images. Mostly the images in natural surface posses low contrast as the features have a low range of reflectance in any waveband which effects the further development process of CAP-LR. CAP-LR generally includes the following steps: preprocessing, feature extraction, classification and recognition. However, blurness and presence of unwanted noise on leaf images result in false classification. Thus image pre-processing such as image enhancement techniques are highly needed to improve the quality of leaf image. Image enhancement is basically improving the interpretability or perception of information in images for human viewers and providing `better' input for other automated image processing techniques [1,5]. During this process, one or more attributes of the image are modified. The choice of attributes and the way they are modified are specific to a given task. Image enhancement techniques are used to highlight certain features (i) increasing the contrast, (ii) changing the brightness level of an image so that the image looks better. In this paper, a hybrid approach [12] that simultaneously removes noise, adjusts contrast and enhances boundaries is presented.