Rancang Bangun Deteksi Objek dengan Metode Filter Warna HSV pada Sistem Klasifikasi Kualitas Biji Kopi Berbasis NVIDIA Jetson Nano

The Post-harvest coffee bean selection plays a crucial role in ensuring optimal bean quality during production processes. Currently, this process is manually conducted in Indonesia. Implementing computer vision can enhance the objectivity of the sorting process through machine vision. An effective object detection system is essential to support a prototype coffee bean quality classification system based on NVIDIA Jetson Nano. The Hue Saturation Value (HSV) color filter method proves effective in detecting objects within a given image frame. Performance evaluation is conducted by assessing the alignment between workflow design and system operation. While the webcam-based object detection system successfully deployed, its effectively identifies coffee bean objects, it faces limitations in detecting smaller, dark-colored beans beyond the specified HSV color threshold. These limitations are attributed to the webcam's specifications, including its rolling shutter, which results in a 'jello effect' when dealing with moving objects

Image-Processing Techniques for the Creation of Presentation-Quality Astronomical Images

The quality of modern astronomical data, the power of modern computers and the agility of current image-processing software enable the creation of high-quality images in a purely digital form. The combination of these technological advancements has created a new ability to make color astronomical images. And in many ways it has led to a new philosophy towards how to create them. A practical guide is presented on how to generate astronomical images from research data with powerful image-processing programs. These programs use a layering metaphor that allows for an unlimited number of astronomical datasets to be combined in any desired color scheme, creating an immense parameter space to be explored using an iterative approach. Several examples of image creation are presented. A philosophy is also presented on how to use color and composition to create images that simultaneously highlight scientific detail and are aesthetically appealing. This philosophy is necessary because most datasets do not correspond to the wavelength range of sensitivity of the human eye. The use of visual grammar, defined as the elements which affect the interpretation of an image, can maximize the richness and detail in an image while maintaining scientific accuracy. By properly using visual grammar, one can imply qualities that a two-dimensional image intrinsically cannot show, such as depth, motion and energy. In addition, composition can be used to engage viewers and keep them interested for a longer period of time. The use of these techniques can result in a striking image that will effectively convey the science within the image, to scientists and to the public.Comment: 104 pages, 38 figures, submitted to A

Analysis of Hue Spectra During Storage of Pepper (Capsicum annuum)

Color information is widely used in non-destructive quality assessment of perishable horticultural produces. The presented work investigated color changes of pepper (Capsicum annuum L.) samples received from retail system. The effect of storage temperature (10±2°C and 24±4°C) on surface color and firmness was analyzed. Hue spectra was calculated using sum of saturations. A ColorLite sph850 (400-700nm) spectrophotometer was used as reference instrument. Dynamic firmness was measured on three locations of the surface: tip cap, middle and shoulder. Significant effects of storage conditions and surface location on both color and firmness were observed. Hue spectra responded sensitively to color development of pepper. Prediction model (PLS) was used to estimate dynamic firmess based on hue spectra. Accuracy was very different depending on the location. Firmness of the tip cap was predicted with the highest accuracy (RMSEP=0.0335). On the other hand, middle region cannot be used for such purpose. Due to the simplicity and rapid processing, analysis of hue spectra is a promising tool for evaluation of color in postharvest and food industry

The effect of visual stimuli on the horribleness of awful sounds.

A mass web-based experiment has been carried out to explore people’s perception of horrible sounds. The advantage of a web-based methodology is that it enables hundreds of thousands of judgements to be obtained over a diverse population. As part of the project, the effect of what people saw on the screen on how they rated the sounds was examined. The sounds were auditioned with images that were either associated or unassociated with the sounds. It was found that images often affected how horrible the sound was perceived to be. For example, the image of finger nails on a blackboard made the associated sound more awful. However, in the case of disgusting sounds, such as the sound of someone eating, the images used had no significant effect on voting behaviour. The colour of the website was also varied. The hue of the website was found to be a significant factor, with a red website making the sounds less horrible than a blue/green website. The brightness and saturation of the website also altered people’s perceptions, with the brighter, more saturated website making the most awful sounds, such as the sound of someone vomiting, less horrible