Internal quality assessment of tomato fruits using image color analysis

Nondestructive optical methods based on image analysis have been used for determining quality of tomato fruit. It is rapid and requires less sample preparation. A samples of fresh tomatoes were picked at different maturity stages, and determining chromaticity values (L*,a*,b*,a*/b*,h˚and ΔE) by image analysis and colorimeter. Total soluble solids (TSS), were measured by refractometer, lycopene extracting and expressed as mg/kg fresh tomato (FW). Results indicated that, during ripening both L*, b*, h˚, and ΔE tendency to decline, opposite tendency was determined with a*, a*/b* ratio, TSS and lycopene content. Chromaticity values have an important impact in internal quality parameters. Where, avg. of TSS, entire class and lycopene content had a positive linear correlation with a*/b* ratio. Contrary correlation was determined between avg. of TSS, entire class and both h˚ and ΔE. Meanwhile, h˚ and ΔE, had a negative logarithmic correlation with lycopene content. On the other hand, there were positive correlation between chromaticity values performed by image analysis technology and colorimeter. Where, on determining avg. of TSS, entire class, and lycopene content, correlations were linear with a*/b* ratio, and logarithmic with ΔE. Meanwhile, h˚ had alogarithmic correlation on determining avg. of TSS, entire class, and exponential correlation on determining lycopene content

A review of chemical ‘spot’ tests: A presumptive illicit drug identification technique

Copyright © 2017 John Wiley & Sons, Ltd. Chemical ‘spot’ tests are a presumptive illicit drug identification technique commonly used by law enforcement, border security personnel, and forensic laboratories. The simplicity, low cost, and rapid results afforded by these tests make them particularly attractive for presumptive identification globally. In this paper, we review the development of these long-established methods and discuss color test recommendations and guidelines. A search of the scientific literature revealed the chemical reactions occurring in many color tests are either not actively investigated or reported as unknown. Today, color tests face many challenges, from the appearance of new psychoactive substances to concerns regarding selectivity, sensitivity, and safety. Advances in technology have seen color test reagents used in digital image color analysis, solid sensors, and microfluidic devices for illicit drug detection. This summarizes current research and suggests the future of presumptive color testing

Basic digital image color analysis for nondestructive testing of setting and curing process of building products: application to thin render layers sprayed at building site

Many building products are put in place in liquid or plastic state. During the first hours and days, the products set and dry, changing their mechanical properties, and their visual aspect also changes in parallel because of the hardening process. In the case of sprayed products, the technical supervisor must know at any time the quality of every sprayed layer and finally determine when it has reached its point of maturity that allows considering it as ready or suitable to receive the next layer. Experimented professionals often use personal visual ability to recognize the evolution of visual colors and surface textures of thin render layers applied on site as capacity to determine this right moment, especially in the case of dry mix sprayed products that harden progressively during curing process. However, these visual assessments are not considered decisive as a technical procedure to assess the evolution of the sprayed product properties. As they are thin layers, it can be considered that the information acquired from their surface is sufficiently representative of their interior qualities. The aim of this study is to correlate information obtained in successive local measurements of humidity and penetration resistance taken on the early surface of a dry mix product just sprayed (portland cement mortar and gypsum plaster) during its setting phase and to compare it with its surface digital color evolution during this process. The goal was to explore whether it is possible to establish a relationship between evolution of resistance penetration and evolution of some digital image basic parameters during the setting and drying period. If this relationship were sufficient, conventional point-to-point contact tests (destructive tests) could be replaced in the future by nondestructive surface visual tests. This is very useful at the building site where there are big surfaces to assess and only a short time to make the right decisions.Peer ReviewedPostprint (author's final draft

A Measurement System for On-line Estimation of Weed Coverage

This paper describes two different solutions for the estimation of weed coverage. Both measuring systems discriminate the weed from the ground by means of the color difference between the weed and ground and can be used to on-line control tractor sprayers in order to reduce weedkiller use. The solutions differ with respect to the sensor type: one solution is based on a digital camera and a computer that analyzes the images and determines the weed amount, while the other simpler solution makes use of two photo detectors and an analog processing system. The camera-based solution provides an uncertainty of a few percentage, while the photo detector-based one, though extremely cheap, has an uncertainty of about 5% and suffers from changes in light conditions, which can alter the estimation

The appearance of mimetic Heliconius butterflies to predators and conspecifics.

Adaptive coloration is under conflicting selection pressures: choosing potential mates and warning signaling against visually guided predators. Different elements of the color signal may therefore be tuned by evolution for different functions. We investigated how mimicry in four pairs of Heliconius comimics is potentially seen both from the perspective of butterflies and birds. Visual sensitivities of eight candidate avian predators were predicted through genetic analysis of their opsin genes. Using digital image color analysis, combined with bird and butterfly visual system models, we explored how predators and conspecifics may visualize mimetic patterns. Ultraviolet vision (UVS) birds are able to discriminate between the yellow and white colors of comimics better than violet vision (VS) birds. For Heliconius vision, males and females differ in their ability to discriminate comimics. Female vision and red filtering pigments have a significant effect on the perception of the yellow forewing band and the red ventral forewing pattern. A behavioral experiment showed that UV cues are used in mating behavior; removal of such cues was associated with an increased tendency to approach comimics as compared to conspecifics. We have therefore shown that visual signals can act to both reduce the cost of confusion in courtship and maintain the advantages of mimicry.ERC, CAPES, STR

A brief network analysis of Artificial Intelligence publication

In this paper, we present an illustration to the history of Artificial Intelligence(AI) with a statistical analysis of publish since 1940. We collected and mined through the IEEE publish data base to analysis the geological and chronological variance of the activeness of research in AI. The connections between different institutes are showed. The result shows that the leading community of AI research are mainly in the USA, China, the Europe and Japan. The key institutes, authors and the research hotspots are revealed. It is found that the research institutes in the fields like Data Mining, Computer Vision, Pattern Recognition and some other fields of Machine Learning are quite consistent, implying a strong interaction between the community of each field. It is also showed that the research of Electronic Engineering and Industrial or Commercial applications are very active in California. Japan is also publishing a lot of papers in robotics. Due to the limitation of data source, the result might be overly influenced by the number of published articles, which is to our best improved by applying network keynode analysis on the research community instead of merely count the number of publish.Comment: 18 pages, 7 figure

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Human hand posture detection and recognition is a challenging problem in computer vision. We introduce an algorithm that is capable to recognize hand posture in a sophisticated background. The system combines two algorithms to achieve better detection rate for hand. Recently Viola et al. in have introduced a rapid object detection scheme; we use this approach to detect the hand posture in the first set of consecutive frames. The chromatic color distribution of skin can be found within this cluster. As the shape of hand posture keep changing in the subsequent frames, the skin regions updated dynamically. The classification of hand posture makes use of static feature for locating and counting hand fingers. Kalman Filter is used to track the face and hand blobs based on their position. In the experiments, we have tested our system in various environments, and results showed effectiveness of the approach