www.ijemr.net ISSN (ONLINE): 2250-0758, ISSN (PRINT): 2394-6962 Volume-6, Issue-2, March-April 2016 International Journal of Engineering and Management Research Page Number: 64-68 Analysis of the Leaf Histogram with HSV-Model Prof. Dr. P.K.Srimani1, K. Nithiyanandhan2 1Director R&D Division, B.U., DSI, Bangalore, Karnataka, INDIA 2Department of Master of Computer & Applications, Brindavan College, Bangalore, Karnataka, INDIA and Research Scholar, Rayalaseema University, Kurnool, Andhra Pradesh, INDIA ABSTRACT results of the present research work include the analysis of Image processing has been proved to be an effective various medicinal leaves through histogram by using the tool for analysis in various fields and applications. The HSV- Model which describes colors in terms of Hue, present study deals with the analysis of medicinal plants like Saturation and Value (brightness). The results are very Peepal Leaf, Betel leaf, Hibiscus Leaf, Karpooravalli etc. by informative. using the techniques of Image Processing. Any disturbance between the elements of human body leads to disease and the Keywords--- Image Processing, Peepal Leaf, Betel Leaf, therapy lies in restoring the balance through the use of Hibiscus Leaf medicinal medicines of natural origin such as herbs and minerals. India is endowed with a rich variety of medicinal plants. The I. INTRODUCTION Introduction to Medicinal Plants: India is a Image processing is a method to convert an country known for ancient scripts, the number system, image into digital form and perform some operations on it, invention of zero and Vedas. Indian Medicines are used by in order to get an enhanced image or to extract some useful about 60 per cent of the world's population. These are not information from it. It is a type of signal dispensation in only used for primary health care not just in rural areas in which input is image, like video frame or photograph and developing countries, but also in developed countries as output may be an image or characteristics associated with well where modern medicines are predominantly used. that image. Usually Image Processing system includes While the traditional medicines are derived from medicinal treating images as two dimensional signals while applying plants, minerals, and organic matter, the herbal drugs are the regular signal processing methods to them. prepared from medicinal plants only. Use of plants as a It is among rapidly growing technologies today, with its source of medicine has been an ancient practice and is an applications in various aspects of business. Image important component of the health care system in India. In Processing forms core research area within engineering the Indian systems of medicine, most practitioners and computer science disciplines too. formulate and dispense their own recipes; hence this Image processing basically includes the following requires proper documentation and research. In west also three steps: the use of herbal medicines is growing with approximately · i) Importing the image with optical scanner or by digital 40 per cent of populations have report the use of herb to photography. treat medical diseases. During the last two decades general · ii) Analyzing and manipulating the image which includes public, academic and government interest in traditional data compression and image enhancement and spotting medicines is growing rapidly due to the increased side patterns that are not the visible to human eyes like satellite effects of the adverse drug reactions and cost factor of the photographs. modern system of medicine. In rural India, 70 per cent of · iii) Output is the last stage in which visible result can alter the population depends on the traditional type of medicine, the image or report that is based on image analysis. 64 Copyright © 2016. Vandana Publications. All Rights Reserved. www.ijemr.net ISSN (ONLINE): 2250-0758, ISSN (PRINT): 2394-6962 error (RMSE) between predicted chlorophyll and chlorophyll measured by CM1000 meter is found to be II. RELATED WORK 1.9334. The paper [6] proposes an efficient computer- The review article [1] emphasizes that on the aided Plant Image Retrieval method based on plant leaf detection of plant disease is a very important factor to images using Shape, Color and Texture features intended prevent serious outbreak. Automatic detection of plant mainly for medical industry, botanical gardening and disease is an essential research topic. Most plant diseases cosmetic industry. Here, they use HSV color space to are caused by fungi, bacteria, and viruses. Fungi are extract the various features of leaves. Log-Gabor wavelet identified primarily from their morphology, with emphasis is applied to the input image for texture feature extraction. placed on their reproductive structures. Then green pixels are masked and removed using specific threshold value, III. PROBLEM SPECIFICATION then the image is segmented and the useful segments are extracted, finally the texture statistics is computed. from The main objectives of the present study is to SGDM matrices. Finally the presence of diseases on the make a detailed analysis of same Indian Medicinal leaves plant leaf is evaluated. in particular Peepal Leaf, Betel Leaf, Karpooravalli, The review article [2] on Leaf color is usually Hibiscus etc by using the techniques of image processing used as a guide for assessments of nutrient status and plant methodologies. Different samples are taken and the health. The propose a new inexpensive, hand-held and experiments are conducted. easy-to-use technique for the detection of chlorophyll content and foliar nitrogen content in plants based on leaf IV. METHODOLOGY color. The algorithm produced superior correlations with the true value of foliar chlorophyll content measured in the In order to make a detailed analysis of the leaves, laboratory when compared with existing non-destructive the following steps are performed and the codes are written methods. in Matlab 7.50 Version. In [3] a review article on Agriculture diseases the ALGORITHM science or practice of farming, including cultivation of the Step 1: Read the image soil for the growing of crops and the rearing of animals to Step 2: Convert into RGB to HSV provide food, wool, and other products. Nitrogen is one of Step 3: Set Image the abundant mineral which plays important role in yield h = hsv(:,1); of crops. The paper aims to introduce software “Nitrate s = hsv(:,2); app”. The software has revolutionized the method to find v = hsv(:,3); the nitrogen content in leaves. Step 4: Finds location of black and white pixels In [4] studies on the Plant pathogens which Step 5: Gets the number of all pixels for each cause disease in plants. Chili, peppers are one of the most color bin important crops is presented in the world. The images are Step 6: To find the number of pixels converted to perceptual spaces [hue, saturation and Step 7: Plots histogram lightness (HSL), hue, saturation, and intensity (HSI) and hue saturation and value (HSV)]. HSI color space was the Figure 1 Code for the analysis of leaves best detected disease. The percentage of disease in the leaf is of 12.42%. HSL and HSV do not expose the exact area Primary Colors: The concept of primary colors of the disease compared to the HSI color space. Finally, is based on the fact that any color can be created by images were analyzed and the disease was known by the combining three colors, white, and black. However, since expert in plant pathology to take were understood colors can be generated directly (e.g., by a display) or by preventive or corrective actions. reflection (e.g., by paint), there are more than one In [5] a study on image analysis is discussed for definition in which set of colors are the "primary colors". the determination of chlorophyll content of leaves of In fact, there are three sets of primary colors. sugarcane plant using the HSV color space. A Liner Hue: A hue, or a "pure" color, is the combination mathematical HSV model is proposed to co-relate with the of two primary colors, where one of the two primary colors chlorophyll content, apart from the simple correlation is at full intensity. The discussion of tinting, shading, and analysis. Among the mean HSV (Hue, Saturation, and tones will make this concept more clear.(Figure 1) Value), the significant co-relation is observed between Saturation and Value parameter with chlorophyll content, while no co-relation is observed with Hue parameter. A good agreement between the predicted and actual chlorophyll content is demonstrated. The root mean square 65 Copyright © 2016. Vandana Publications. All Rights Reserved. www.ijemr.net ISSN (ONLINE): 2250-0758, ISSN (PRINT): 2394-6962 tinting. Thus desaturated colors have increasing total intensity. For this reason, the CSS3 standard plans to support RGB and HSL but not HSV. HSL: The HSL model describes colors in terms of hue, saturation, and lightness (also called luminance). (Note: the definition of saturation in HSL is substantially different from HSV.) The model has two prominent properties: • The transition from black to a hue to white is symmetric and is controlled solely by increasing Figure 1. Color Wheel lightness Shading and tinting are controlled by a RGB Color Wheel: One of the interesting single value, lightness aspects of the mind's interpretation of color is that it sees • Decreasing saturation transitions to a shade of the relationship between colors in a circular manner. A gray dependent on the lightness, thus keeping the color wheel is a tool that provides