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Power centroid radar (PC-Radar) is a fast and powerful adaptive radar scheme that naturally surfaced from the recent discovery of the time-dual for information theory which has been named "latency theory." Latency theory itself wa...
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Power centroid radar (PC-Radar) is a fast and powerful adaptive radar scheme that naturally surfaced from the recent discovery of the time-dual for information theory which has been named "latency theory." Latency theory itself was born from the universal cybernetics duality (UC-Duality), first identified in the late 1970s, that has also delivered a time dual for thermodynamics that has been named "lingerdynamics" and anchors an emerging lifespan theory for biological systems. In this paper the rise of PC-Radar from the UC-Duality is described. The development of PC-Radar, US patented, started with Defense Advanced Research Projects Agency (DARPA) funded research on knowledge-aided (KA) adaptive radar of the last decade. The outstanding signal to interference plus noise ratio (SINR) performance of PC-Radar under severely taxing environmental disturbances will be established. More specifically, it will be seen that the SINR performance of PC-Radar, either KA or knowledge-unaided (KU), approximates that of an optimum KA radar scheme. The explanation for this remarkable result is that PC-Radar inherently arises from the UC-Duality, which advances a "first principles" duality guidance theory for the derivation of synergistic storage-space/computational-time compression solutions. Real-world synthetic aperture radar (SAR) images will be used as prior-knowledge to illustrate these results.
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Statistical physics bridges for latency information theory (LIT) are revealed in this second paper of a three paper series that include the discovery of the time dual of thermodynamics. LIT is the universal guidance theory for eff...
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Statistical physics bridges for latency information theory (LIT) are revealed in this second paper of a three paper series that include the discovery of the time dual of thermodynamics. LIT is the universal guidance theory for efficient system designs that has inherently surfaced from the confluence of five ideas. They are: 1) The source entropy. and channel capacity performance bounds of Shannon's mathematical theory of communication; 2) The latency time (LT) certainty of Einstein's relativity theory; 3) The information space (IS) uncertainty of Heisenberg's quantum physics; 4) The black hole Hawking radiation and its Boltzmann thermodynamics entropy S in SI J/K; and 5) The author's 1978 conjecture of a structural-physical LT-certainty/IS-uncertainty duality for stochastic control. LIT is characterized by a four quadrants revolution with two mathematical-intelligence quadrants and two physical-life ones. Each quadrant of LIT is assumed to be physically independent of the others and guides its designs with an entropy if it is IS-uncertain and an ectropy if it is LT-certain. While LIT's physical-life quadrants I and III address the efficient use of life time by physical signal movers and of life space by physical signal retainers, respectively, its mathematical-intelligence quadrants II and IV address the efficient use of intelligence space by mathematical signal sources and of processing time by mathematical signal processors, respectively.. Seven results are stated next that relate to the revelation of statistical physics bridges for LIT. They are: 1) Thermodynamics, a special case of statistical physics, has a time dual named lingerdynamics; 2) Lingerdynamics has a dimensionless lingerdynamics-ectropy Z that is the LT-certainty dual of a dimensionless thermodynamics-entropy, and like thermodynamics has four physical laws that drive the Universe; 3) S advances a bridge between quadrant Ws source-entropy H in bit units and quadrant III's retainer-entropy N in SI m~2 units; 4) Z advances a bridge between quadrant I's mover-ectropy A in SI secs and quadrant IV's processor-ectropy K in binary operator (bor) units; 5) Statistical physics bridges are discovered between the LIT entropies and the LIT ectropies; 6) Half of the statistical physics bridges between the LIT entropies and LIT ectropies are found to be medium independent, thus yielding the same entropy-ectropy relationships for black holes, ideal gases, biological systems, etc.; and 7) A medium independent quadratic relationship i=l(M/ΔM)~2 relates the lifespan r of a retained mass M to the ratio of M to the fractional mass AM that escapes it every 1 seconds, e.g., for a human with M = 70 kg, expected lifespan of i=83.9 years (or 2.65 Gsec), l=1 day (or 86.4 ksec), its daily escaping mass is given by ΔM=0.4 kg. In turn, this requires him/her to consume 2,000 kcal per day (i.e., 5,000 kcal/kg times 0.4 kg) to replace the 0.4 kg lost from day to day which correlates well with expectations.
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With the latest advances in image sensor technology, cameras are able to generate video with tens of megapixels per frame. These high resolution videos streams offer great potential to be used in the surveillance domain. For groun...
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With the latest advances in image sensor technology, cameras are able to generate video with tens of megapixels per frame. These high resolution videos streams offer great potential to be used in the surveillance domain. For ground based systems, gigapixel streams are already used with great effect as illustrated by the ICME 2019 crowd counting challenge. However, for Unmanned Aerial Vehicles (UAVs), this vast stream of data exceeds the limit of transmission bandwidth to send this data back to the ground. On board data analysis and selection is thus required to use and benefit from high resolution cameras. This paper presents a result of the CAVIAR project, where a combination of hardware and algorithms was designed to answer the question: "how to exploit a high resolution high frame rate camera on board a UAV?'. With the associated size, weight and power limitations, we implement data reduction by deploying deep learning on hardware to find the relevant information and transmit it to an operator station. The proposed solution aims at employing the high resolution potential of the sensor only onto objects of interest. We encode and transmit the identified regions containing those objects of interest (ROI) at the original resolution and framerate, while also transmitting the downscaled background to provide context for an operator. We demonstrate using a 35 fps, 65 Megapixel camera that this set-up indeed saves considerable bandwidth while retaining all important video data at high quality at the same time.
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Universal cybernetics is the study of control and communications in living and non-living systems. In this paper the universal cybernetics duality principle (UCDP), first identified in control theory in 1978 and expressing a cyber...
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Universal cybernetics is the study of control and communications in living and non-living systems. In this paper the universal cybernetics duality principle (UCDP), first identified in control theory in 1978 and expressing a cybernetic duality behavior for our universe, is reviewed. The review is given on the heels of major prizes given to physicists for their use of mathematical dualities in solving intractable problems in physics such as those of cosmology's 'dark energy', an area that according to a recent New York Times article has become "a cottage industry in physics today". These dualities are not unlike those of our UCDP that are further enhanced with physical dualities. For instance, in 2008 the UCDP guided us to the derivation of the laws of retention in physics as the space-penalty dual of the laws of motion in physics, including the dark energy thought responsible for the observed increase of the volume of our Universe as it ages. The UCDP has also guided us to the discovery of significant results in other fields such as: 1) in matched processors for quantized control with applications in the modeling of central nervous system (CNS) control mechanisms; 2) in radar designs where the discovery of latency theory, the time-penalty dual of information-theory, has led us to high-performance radar solutions that evade the use of 'big data' in the form of SAR imagery of the earth; and 3) in unveiling biological lifespan bounds where the life-expectancy of an organism is sensibly predicted through linger dynamics, the identified time-penalty dual of thermodynamics, which relates its adult lifespan to either: a. the ratio of its body size to its nutritional consumption rate; or b. its specific heat-capacity; or c. the ratio of its nutritional consumption rate energy to its entropic volume energy, a type of dark energy that is consistent with the observed decrease in the mass density of the organism as it ages.
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Camera phones are ubiquitous, and consumers have been adopting them faster than any other technology in modem history. When connected to a network, though, they are capable of more than just picture taking: Suddenly, they gain acc...
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Camera phones are ubiquitous, and consumers have been adopting them faster than any other technology in modem history. When connected to a network, though, they are capable of more than just picture taking: Suddenly, they gain access to the power of the cloud. We exploit this capability by providing a series of image-based personal advisory services. These are designed to work with any handset over any cellular carrier using commonly available Multimedia Messaging Service (MMS) and Short Message Service (SMS) features. Targeted at the unsophisticated consumer, these applications- must be quick and easy to use, not requiring download capabilities or preplanning. Thus, all application processing occurs in the back-end system (i.e., as a cloud service) and not on the handset itself. Presenting an image to an advisory service in the cloud, a user receives information that can be acted upon immediately. Two of our examples involve color assessment — selecting cosmetics and home decor paint palettes; the third provides the ability to extract text from a scene. In the case of the color imaging applications, we have shown that our service rivals the advice quality of experts. The result of this capability is a new paradigm for mobile interactions — image-based information services exploiting the ubiquity of camera phones.
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Since its introduction more than six decades ago by Claude E. Shannon information theory has guided with two performance bounds, namely source-entropy II and channel capacity C, the design of sourced intelligence-space compressors...
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Since its introduction more than six decades ago by Claude E. Shannon information theory has guided with two performance bounds, namely source-entropy II and channel capacity C, the design of sourced intelligence-space compressors for communication systems, where the units of intelligence-space are `mathematical' binary digit (bit) units of a passing of time uncertainty nature. Recently, motivated by both a real-world radar problem treated in the first part of the present paper series, and previous uncertainty/certainty duality studies of digital-communication and quantized-control problems by the author, information theory was discovered to have a `certainty' time-dual that was named latency theory. Latency theory guides with two performance bounds, i.e. processor-ectropy K and sensor consciousness F the design of processing intelligence-time compressors for recognition systems, where the units of intelligence-time are `mathematical' binary operator (bor) units of a configuration of space certainty nature. Furthermore, these two theories have been unified to form a mathematical latency-information theory (M-LIT) for the guidance of intelligence system designs, which has been successfully applied to real-world radar. Also recently, M-LIT has been found to have a physical LIT (P-LIT) dual that guides life system designs. This novel physical theory addresses the design of motion life-time and retention life-space compressors for physical signals and also has four performance bounds. Two of these bounds are mover-ectropy A and channel-stay T for the design of motion life-time compressors for communication systems. An example of a motion life-time compressor is a laser system, inclusive of a network router for a certainty, or multi-path life-time channel. The other two bounds are retainer-entropy Nand sensor scope I for the design of retention life-space compressors for recognition systems. An example of a retention life-space compressor is a silicon semiconductor crystal, inclusive of a leadless chip carrier for an uncertainty, or noisy life-space sensor. The eight performance bounds of our guidance theory for intelligence and life system designs will be illustrated with practical examples. Moreover, a four quadrants (quadrants I and III for the two physical theories and quadrants II and IV for the two mathematical ones) LIT revolution is advanced that highlights both the discovered dualities and the fundamental properties of signal compressors leading to a unifying communication embedded recognition (CER) system architecture.
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In this first part of the latest latency-information theory (LIT) and applications paper series powerful and fast `knowledge-unaided' power-centroid (F-KUPC) radar is revealed. More specifically, it is found that for real-world ai...
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In this first part of the latest latency-information theory (LIT) and applications paper series powerful and fast `knowledge-unaided' power-centroid (F-KUPC) radar is revealed. More specifically, it is found that for real-world airborne moving target indicator radar subjected to severely taxing environmental conditions F-KUPC radar approximates the signal to interference plus noise ratio (SINR) radar performance derived with more complex knowledge-aided power-centroid (KAPC) radar. KAPC radar was discovered earlier as part of DARPA's 2001-2005 knowledge-aided sensor signal processing expert reasoning (KASSPER) Program and outperforms standard prior-knowledge radar schemes by several orders of magnitude in both the compression of sourced intelligence-space of prior-knowledge, in the form of SAR imagery, and the compression of processing intelligence-time of the associated clutter covariance processor, while also yielding an average SINR radar performance that is approximately 1dB away from the optimum. In this paper, it is shown that the average SINR performance of significantly simpler F-KUPC radar emulates that of KAPC radar and, like KAPC radar, outperforms a conventional knowledge-unaided sample covariance matrix inverse radar algorithm by several dBs. The matlab simulation programs that were used to derive these results will become available in the author's Web site.
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Manual inspections of glass facade of high rising buildings are expensive, time-consuming and potentially life-threatening for both inspectors and pedestrians on the street. Advances in machine learning for image/video analysis an...
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Manual inspections of glass facade of high rising buildings are expensive, time-consuming and potentially life-threatening for both inspectors and pedestrians on the street. Advances in machine learning for image/video analysis and availability of affordable unmanned aerial vehicles (UAVs) with onboard video recording and processing sensors provide opportunities for smart, safe and automatic glass facade inspections. This paper is concerned with developing an effective solution for recognizing cracked glass panels, which can be installed on board a UAV. From static 2D photographic images, the proposed solution analyzes textural patterns of smooth glass surface and crack segments, linearity of detected crack segments, geometrical characteristics of crack curvatures and the crack pixel patterns, captures these discriminative features for glass cracks using Uniform Local Binary Pattern (ULBP), histograms of linearity, geometrical curvature descriptors with fixed length connected pixel configurations, and accordingly classifies images of cracked and non-cracked glass panels using a kNN classifier. Experimental results with images of different resolutions acquired by a UAV drone in a real office building setting and images collected through Google search demonstrate that the proposed solution achieves promising results with accuracy rates in excess of 80% and even as high as 91% despite the presence of reflections.
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Region growing is defined as a procedure of finding regions containing user defined objects of interest.
Growing region is a vital phase for various image processing applications. Growing region
in images has been very challengi...
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Region growing is defined as a procedure of finding regions containing user defined objects of interest.
Growing region is a vital phase for various image processing applications. Growing region
in images has been very challenging as it is the base for further image analysis,interpretation
and classification.Region growing varies for different purpose of aim.However,the identified region
are widely used for various domain-skin detection, detect object in image,hand gesture detection
etc.In this paper,the main concentration is to defining region of interest from an image
based on skin detection.A clustering method was used.Skin detection can be used as a preprocessing
step for several applications included but not limited to various Human Computer Interaction
(HCI) tasks.However,skin detection is a challenging problem due to sparse variations of skin
tone of human. Skin tone can be confused with background color,attire color,ethnicity,individual
characteristics-age,sex,body parts,makeup,hair color,presence of non-human objects and camera
calibration.Besides that,lightning conditions also plays a vital role. Researchers have been working
tirelessly for an ecient skin detection method but those are not beyond limitations.Various approach
including pixel wise threshold for various color spaces,segmentation, face and hand detection
based approaches are proposed.But it still lacks from a method which can be applied for all types
of skin detection. In this paper,a novel skin detection method is proposed which is free from any
manual threshold values and automatically define number of clusters.
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摘要 :
Region growing is defined as a procedure of finding regions containing user defined objects of interest.
Growing region is a vital phase for various image processing applications. Growing region
in images has been very challenging...
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Region growing is defined as a procedure of finding regions containing user defined objects of interest.
Growing region is a vital phase for various image processing applications. Growing region
in images has been very challenging as it is the base for further image analysis,interpretation
and classification.Region growing varies for different purpose of aim.However,the identified region
are widely used for various domain-skin detection, detect object in image,hand gesture detection
etc.In this paper,the main concentration is to defining region of interest from an image
based on skin detection.A clustering method was used.Skin detection can be used as a preprocessing
step for several applications included but not limited to various Human Computer Interaction
(HCI) tasks.However,skin detection is a challenging problem due to sparse variations of skin
tone of human. Skin tone can be confused with background color,attire color,ethnicity,individual
characteristics-age,sex,body parts,makeup,hair color,presence of non-human objects and camera
calibration.Besides that,lightning conditions also plays a vital role. Researchers have been working
tirelessly for an e cient skin detection method but those are not beyond limitations.Various approach
including pixel wise threshold for various color spaces,segmentation, face and hand detection
based approaches are proposed.But it still lacks from a method which can be applied for all types
of skin detection. In this paper,a novel skin detection method is proposed which is free from any
manual threshold values and automatically define number of clusters.
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