The feasibility of animal source foods’ color measurement using CVS

Color assessment of animal source foods was investigated using a computer vision system (CVS) and a traditional colorimeter. With the same measurement conditions, color readings varied between these two approaches. The color measured by CVS was highly similar to the actual color of animal source foods, and ranged from 75.0%-100.0% of actual colors, whereas colors read by a Minolta colorimeter showed non-typical appearances. The CVS-obtained colors were more similar to the color of food visualized on the monitor, compared to colorimeter-generated color chips. Considering these results, it could be concluded that the CVS is a superior alternative for replacing traditional devices by providing better accuracy.

Spatial Induction in Color Scission

An exception to the rule that only one color is seen at every retinotopic location happens when a bounded colored transparency or spotlight is seen on a differently colored surface. Despite the spectrum of the light from each retinotopic location being an inextricable multiplication of illumination, transmission, and reflectance spectra, we seem to be able to scission the information into background and transparency/spotlight colors. Visual cues to separating overlay and overlaid layers have been enumerated, but neural mechanisms that extract veridical colors for overlays have not been identified. Here, we demonstrate that spatial induction contributes to color scission by shifting the color of the overlay toward the actual color of the filter. By alternating filter and illumination spectra, we present naturalistic simulations where isomeric disks appear to be covered by filters/spotlights of near veridical colors, depending solely on the surrounding illumination. This previously unrecognized role for spatial induction suggests that color scission employs some general purpose neural mechanisms.

Early, color-specific neural responses to object color knowledge

Some familiar objects are associated with specific colors, e.g., rubber ducks with yellow. Whether and at what stage neural responses occur to these color associations remain open questions. We tested for frequency-tagged electroencephalogram (EEG) responses to periodic presentations of yellow-associated objects, shown among sequences of non-periodic blue-, red-, and green-associated objects. Both color and grayscale versions of the objects elicited yellow-specific responses, indicating an automatic activation of color knowledge from object shape. Follow-up experiments replicated these effects with green-specific responses, and demonstrated modulated responses for incongruent color-object associations. Importantly, the onset of color-specific responses was as early to grayscale as actually colored stimuli (before 100 ms), the latter additionally eliciting a conventional later response (approximately 140-230 ms) to actual stimulus color. This suggests that the neural representation of familiar objects includes both diagnostic shape and color properties, such that shape can elicit associated color-specific responses before actual color-specific responses occur.

Predictive Modeling of a Leaf Conceptual Midpoint Quasi-Color (CMQ) Using an Artificial Neural Network

The color of plant leaves is moderated by the content of pigments, which can show considerable dorsiventral distribution. Two typical examples are leafy vegetables and ornamentals, wherein red and green color surfaces can be seen on the same leaf. The proof of concept is provided for predictive modeling of a leaf conceptual mid-point quasi-color (CMQ) from the content of pigments. The CMQ idea is based on the hypothesis that the content of pigments in leaves is associated with the combined color from both surfaces. The CMQ, which is calculated from CIELab color coordinates at adaxial and abaxial antipodes, is thus not an actual color, but a notion that can be used in modeling. The CMQ coordinates, predicted from the content of chlorophylls and anthocyanins by means of an artificial neural network (ANN), matched well with the CMQ coordinates empirically found on photosynthetically active leaves of lettuce (Lactuca sativa L.), but also with other plant species with comparable leaf attributes. Modeled values of lightness (qL*) decreased with the increasing content of both pigments, while the redness or greenness (qa*) and yellowness or blueness (qb*) of the CMQ were affected more by a relative content of chlorophylls and anthocyanins in leaves. The highest vividness of quasi-colors (qC*) was modeled for leaves with a high content of either pigment alone. The model predicted a substantially duller quasi-color for leaves with chlorophylls and anthocyanins present together, particularly when both pigments were present at very high levels.

Image Inpaint Using Patch Sparsity

The process of removing the specific object or area or repairing the damaged area in an image is known as image inpainting. This algorithm [5] is proposed for removing objects from digital image. The challenge is to fill in the hole that is left behind in a visually plausible way. We first note that patch sparsity based synthesis contains the essential process required to replicate both texture and structure [8]; the success of structure propagation however is highly dependent on the order in which the filling proceeds. We propose a best algorithm in which the confidence in the synthesized pixel values is propagated in a manner similar to the propagation of information in inpainting.The actual color values are computed using patch sparsity based synthesis. In this paper the simultaneous propagation of texture and structure information [2] is achieved by a single, efficient algorithm. For best results selected image should have sufficient background information

What Color Does the Consumer See? Perceived Color Differences in Plastic Products in an LED-Lit Environment

To attract customers and increase market opportunities, retailers frequently use lighting to highlight the color of their products. However, differences between perceived and actual color, triggered by display lighting, can motivate buyers to discard products after purchase. Few studies have been reported on differences in perceived color, caused by LEDs. This study focuses on two correlated color temperatures (2800 K, 4000 K) and illuminance levels (500 lx, 1500 lx) to create four LED-lit environments, and measures the differences in the color perceived by 20 observers on acrylonitrile–butadiene–styrene (ABS) plastics, with different surfaces, under these four environments. The results reveal that correlated color temperature results in larger perceived differences in color than illuminance, and the effects of LED light sources on green and yellow ABS plastic products are more obvious than their effects on red and blue products. One possible reason for this can be attributed to the visual sensitivity effect of human eyes. The results of this study can serve as a reference for designers fabricating ABS plastic products for practical lighting applications, and improving the role of LED lighting in sustainable development.

Image Inpaint Using Patch Sparsity

The process of removing the specific object or area or repairing the damaged area in an image is known as image inpainting. This algorithm [5] is proposed for removing objects from digital image. The challenge is to fill in the hole that is left behind in a visually plausible way. We first note that patch sparsity based synthesis contains the essential process required to replicate both texture and structure [8]; the success of structure propagation however is highly dependent on the order in which the filling proceeds. We propose a best algorithm in which the confidence in the synthesized pixel values is propagated in a manner similar to the propagation of information in inpainting.The actual color values are computed using patch sparsity based synthesis. In this paper the simultaneous propagation of texture and structure information [2] is achieved by a single, efficient algorithm. For best results selected image should have sufficient background information.

Implementasi Pengolahan Citra Digital Sebagai Pengukur Nilai Resistor Pada Sistem Pemindai Resistor Berbasis Android

AbstrakSalah satu gadget yang sering digunakan adalah telepon pintar berbasis Android. Android bersifat Open Source sehingga memungkinkan pengguna dan pengembang dalam mengoperasikan maupun membuat aplikasi berbasis Android. Ada berbagai macam permasalahan yang membutuhkan citra sebagai masukan atau input sistem dikarenakan keterbatasan manusia dalam hal kecepatan memproses suatu fungsi matematis maupun algoritma pendukung didalamnya, selain itu juga masalah waktu dan lain sebagainya. Salah satu sistem yang membutuhkan citra sebagai masukannya adalah penentuan nilai resistor berdasarkan gelang warna. Untuk melakukan seleksi warna digunakan metode segmentasi warna pemodelan warna HSV. Dengan menggunakan model warna HSV dapat menjadi model warna yg dapat digunakan sebuah sistem untuk menentukan nilai warna resistor, karena komponen nilai hue adalah representasi dari nilai warna yang sebenarnya. Hal ini didukung dengan saturation yang berfungsi sebagai tingkat kejenuhan suatu warna dan nilai value sebagai nilai kecerahan warna. Uji coba sistem dilakukan dengan pengujian pengaruh intensitas cahaya dan jarak pendeteksian antara kamera dan resistor.Hasil dari penelitian ini berupa sebuah implementasi pengolahan citra digital sebagai pengukur nilai resistor. Hasil terbaik dicapai dengan kondisi ruangan pada intensitas cahaya lampu antara 400 lux hingga 1200 lux dengan jarak pendeteksian antar kamera dan resistor yaitu maksimal 20 cm. Kata kunci— pengolahan citra digital, Android, resistor, HSV, intensitas cahaya, java AbstractOne of the gadget that is often used is Android smart phones. Android is an OpenSource, it could help user and developer to operate and develop Android Application. There are several problems that need image as an input system, it is caused by the humas’s ability in doing some mathematic functions or supported algorythm. To make the selection color used HSV color space. By using HSV color space allows a system to determine the color value resistor, because the hue value of the component is a representation of the actual color value. This is supported by the saturation level that serves as a color saturation and value as a brightness of color.The results of this research is an implementation of digital image processing as a measure of the value of the resistor. The system is tested by the influence of light intensity and the distance between the camera and resistor. The best results were achieved with the conditions of the room in light intensity between 400 lux to 1200 lux the detection distance between the camera and resistor is 20 cm of maximum value. Keywords—digital image processing, Android, resitor, HSV, light intensity, java

Color Reproduction Experiment of Different Order Polynomial Regression Algorithm

Digital camera is widely used in the data collection of objective and background in the field of pattern design and supervisory controlling. However, the color in digital photo copied from camera is not in accord with the actual color of objective, which affects the accuracy of design pattern. The polynomial regression algorithm is widely used in color reproduction of image input and output area. The accuracy of color reproduction is related to the different order. Therefore, the field experiment is developed. The application indicates that the performance of four order polynomial regression color reproduction is the best algorithms and it can be used in color reproduction.