INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH VOLUME 9, ISSUE 02, FEBRUARY 2020 ISSN 2277-8616 4832 IJSTR©2020 www.ijstr.org Bell Pepper And Chili Pepper Classification: An Application Of Image Processing And Fuzzy Logic Eldrin James Olaes, Edwin R. Arboleda, Jesusimo L. Dioses Jr. and Rhowel M. Dellosa Abstract: Bell pepper is often called sweet pepper and capsicum in other countries. Peppers are well-known for their different colors and uses. Capsicum peppers contain abundant antioxidants and vitamin C. In comparison to red peppers, it has nine times the level of carotene, such as lycopene which is claimed to improved heart health and reduce cancer risk. While, chili pepper, better known as ―Siling Labuyo‖ in the Philippines, is the fruit from the Genus capsicum plant, a member of the nightshade family, Solanaceae. These two kinds of pepper are commonly used as an ingredient for a different type of foods in the Philippines. Bell pepper is typically used in Filipino recipes to enhance its flavor and makes it smell better, while chili peppers are used to enhance the spiciness of the food. In this paper, the methods to be used in classifying differences of the seeds of bell pepper and chili pepper are image processing, fuzzy logic and K nearest neighbor. The morphological features of the seeds such as area, equivalent diameter, perimeter, and roundness in the gathered data from 60 samples of bell pepper and chili pepper seeds have been analyzed to classify bell pepper and chili pepper’s seeds characteristics. The fuzzy logic has been employed to determine the degrees of truth between truth and false instead of the common that only identifies truth and false. MATLAB toolbox will be utilized for the study. The areas, equivalent diameter, perimeter, and roundness will be used as inputs to Mamdai Fuzzy interference to formulate rules and come up to an output that will classify whether the seeds are bell pepper or chili pepper. Index Terms: Bell pepper, chili pepper, fuzzy interference, fuzzy logic, image processing, K nearest neighbor, Matlab ——————————  —————————— 1. INTRODUCTION Bell peppers are fruits with a beautiful shape and different colors varying from green, red, yellow, orange, purple, brown to black [1]–[4]. Even though they have different colors, they are all the same kind of plant known as Capsicum annum. It is famous for its health content [5]. It contains vitamin C, which improves the immune system, prevents infections, increases the growth and repair of tissue, and helps in avoiding cancer [6]. It also has vitamin A that is good in improving eyesight, enhancing the lung function, and likewise enhances the immune system [7]. Furthermore, it contains nutrients that prevent prostate and breast cancer such as Lycopene, and nutrients that prevent cataracts and muscle degeneration such as lutein and zeaxanthin [8]. On the other hand, chili pepper, are one of the very popular spices known for its medicinal and health benefiting properties despite their fiery hotness [9]. It is considered one of the most important commercial spice crops [10]. Sampling and testing of seed observe standard procedures. These procedures are made by ISTA to assess seeds going in international trade [11]. In this study image processing and fuzzy logic were used for the identification of bell pepper and chili pepper. After extracting the features of the sample seeds, it will undergo an intelligent recognition algorithm applying fuzzy logic. Fuzzy logic identifies the degrees of truth instead of the common that only identify completely truth and completely false [12]. iabetes and other diseases which will minimize their expenses. 2 FEATURE EXTRACTION After capturing the samples, bell pepper and chili pepper classification undergo through five steps namely; pre- processing, image segmentation, feature extraction which then undergo the fuzzy logic algorithm to recognize and classify the bell pepper accordingly[13], [14]. Fig 1. Block Diagram of the Bell pepper classification system 2.1 Digital Image Scanning Each image used has at least 30 samples of seeds because seeds do not contain a large area and place the samples in a bond paper. A light was placed underneath the bond paper to remove the shadow of the seeds and lessen its noise. And also, it will be helpful in improving the accuracy of the morphology features [15]. The camera used has 16 megapixels and is placed 5 inches above the seeds. Figure 2 and 3 below shows the original image of the bell pepper seeds and chili pepper seeds. ————————————————  Eldrin James Olaes is from the Department of Computer and Electronics Engineering , Cavite State University, Philippines, Indang, Cavite.  Edwin R. Arboleda is from the Department of Computer and Electronics Engineering , Cavite State University, Philippines, Indang, Cavite..  Jesusimo L. Dioses Jr. is from Isabela State University  Rhowel M. Dellosa is from Asia Technological School of Science and Arts Image Acquisition Pre- Processing Image Segmentation Feature Extraction Fuzzy Logic Algorithm Bell pepper and Chili pepper Classification