An automatic intelligent system for the colour and texture inspection of bakery products is proposed.In this system,advance classification technique featuring Support Vector Machine and biologically inspired HMAX base...An automatic intelligent system for the colour and texture inspection of bakery products is proposed.In this system,advance classification technique featuring Support Vector Machine and biologically inspired HMAX based shape descriptor integrated with biologically plausible RGB Opponent-Colour-Channel Descriptor is used to classify bakery products to their respective classes based on the shape and based on their colour referring to different baking durations. The results of this paper are compared with other methods for the automatic bakery products inspection. It is discovered that biologically inspired computer vision models performs accurately and efficiently as compared to the computer vision models which are not biologically plausible,in the bakery products quality inspection. It is also discovered that the One Versus One SVM and Directed Acyclic Graph SVM acquired the maximum accurate classification rate. The proposed method acquired classification accuracy of 95% and 100% for the biscuit shape and biscuit colour recognition,respectively. The proposed method is also consistently stable and invariant. This shows that the biologically inspired computer vision models have the capability to replace existing inspection methods as more reliable and accurate alternative.展开更多
IN his grade two at middle school, Wang Jianming took part in a study competition, and won first place in physics. The composition he wrote was chosen as a model essay. This first experience
Previous research has shown that ocular dominance can be biased by prolonged attention to one eye.The ocular-opponency-neuron model of binocular rivalry has been proposed as a candidate account for this phenomenon.Yet...Previous research has shown that ocular dominance can be biased by prolonged attention to one eye.The ocular-opponency-neuron model of binocular rivalry has been proposed as a candidate account for this phenomenon.Yet direct neural evidence is still lacking.By manipulating the contrast of dichoptic testing gratings,here we measured the steady-state visually evoked potentials(SSVEPs)at the intermodulation frequencies to selectively track the activities of ocular-opponency-neurons before and after the“dichoptic-backward-movie”adaptation.One hour of adaptation caused a shift of perceptual and neural ocular dominance towards the unattended eye.More importantly,we found a decrease in the intermodulation SSVEP response after adaptation,which was significantly greater when high-contrast gratings were presented to the attended eye than when they were presented to the unattended eye.These results strongly support the view that the adaptation of ocular-opponency-neurons contributes to the ocular dominance plasticity induced by prolonged eye-based attention.展开更多
Drogue detection is one of the challenging tasks in autonomous aerial refueling due to the requirement for accuracy and rapidity.Saliency detection based on image intrinsic cues can achieve fast detection,but with poo...Drogue detection is one of the challenging tasks in autonomous aerial refueling due to the requirement for accuracy and rapidity.Saliency detection based on image intrinsic cues can achieve fast detection,but with poor accuracy.Recent studies reveal that optimization-based methods provide accurate and quick solutions for saliency detection.This paper presents a hybrid pigeon-inspired optimization method,the optimized color opponent,that aims to adjust the weight of color opponent channels to detect the drogue region.It can optimize the weights in the selected aerial refueling scene offline,and the results are applied for drogue detection in the scene.A novel algorithm aggregated by the optimized color opponent and robust background detection is presented to provide better precision and robustness.Experimental results on benchmark datasets and aerial refueling images show that the proposed method successfully extracts the saliency region or drogue and exhibits superior performance against the other saliency detection methods with intrinsic cues.The algorithm designed in this paper is competent for the drogue detection task of autonomous aerial refueling.展开更多
This paper presents a biologically inspired local image descriptor that combines color and shape features. Compared with previous descriptors, red-cyan cells associated with L, M, and S cones (L for long, M for mediu...This paper presents a biologically inspired local image descriptor that combines color and shape features. Compared with previous descriptors, red-cyan cells associated with L, M, and S cones (L for long, M for medium, and S for short) are used to indicate one of the opponent color channels. Stepping forward from state-of-the-art color feature extraction, we exploit a new approach to compute the color orientation and magnitudes of three opponent color channels, namely, red-green, blue-yellow, and red-cyan, in two-dimensional space. Color orientation is calculated in histograms with magnitude weighting. We linearly concatenate the four-color-opponent-channel histogram and scale-invariant-feamre-transform histogram in the final step. We apply our biologically inspired descriptor to describe the local image feature. Quantitative comparisons with state-of-the-art descriptors demonstrate the significant advantages of maintaining invariance to photometric and geometric changes in image matching, particularly in cases, such as illumination variation and image blurring, where more color contrast information is observed.展开更多
基金Sponsored by the National Natural Science Foundation of China(Grant Nos.11572084,11472061,71371046 and 61603088)the Fundamental Research Funds for the Central Universities and DHU Distinguished Young Professor Program(Grant No.16D210404)the China Scholarship Council(CSC)
文摘An automatic intelligent system for the colour and texture inspection of bakery products is proposed.In this system,advance classification technique featuring Support Vector Machine and biologically inspired HMAX based shape descriptor integrated with biologically plausible RGB Opponent-Colour-Channel Descriptor is used to classify bakery products to their respective classes based on the shape and based on their colour referring to different baking durations. The results of this paper are compared with other methods for the automatic bakery products inspection. It is discovered that biologically inspired computer vision models performs accurately and efficiently as compared to the computer vision models which are not biologically plausible,in the bakery products quality inspection. It is also discovered that the One Versus One SVM and Directed Acyclic Graph SVM acquired the maximum accurate classification rate. The proposed method acquired classification accuracy of 95% and 100% for the biscuit shape and biscuit colour recognition,respectively. The proposed method is also consistently stable and invariant. This shows that the biologically inspired computer vision models have the capability to replace existing inspection methods as more reliable and accurate alternative.
文摘IN his grade two at middle school, Wang Jianming took part in a study competition, and won first place in physics. The composition he wrote was chosen as a model essay. This first experience
基金supported by the Ministry of Science and Technology of China(2021ZD0203800)the National Natural Science Foundation of China(31871104 and 31830037).
文摘Previous research has shown that ocular dominance can be biased by prolonged attention to one eye.The ocular-opponency-neuron model of binocular rivalry has been proposed as a candidate account for this phenomenon.Yet direct neural evidence is still lacking.By manipulating the contrast of dichoptic testing gratings,here we measured the steady-state visually evoked potentials(SSVEPs)at the intermodulation frequencies to selectively track the activities of ocular-opponency-neurons before and after the“dichoptic-backward-movie”adaptation.One hour of adaptation caused a shift of perceptual and neural ocular dominance towards the unattended eye.More importantly,we found a decrease in the intermodulation SSVEP response after adaptation,which was significantly greater when high-contrast gratings were presented to the attended eye than when they were presented to the unattended eye.These results strongly support the view that the adaptation of ocular-opponency-neurons contributes to the ocular dominance plasticity induced by prolonged eye-based attention.
基金This work was partially supported by Science and Technology Innovation 2030-Key Project of“New Generation Artificial Intelligence”,China(No.2018AAA0102403)the National Natural Science Foundation of China(Nos.U1913602,T2121003,91948204,62103040,and U20B2071)the Open Fund/Postdoctoral Fund of the Laboratory of Cognition and Decision Intelligence for Complex Systems,Institute of Automation,Chinese Academy of Sciences(No.CASIA-KFKT-08).
文摘Drogue detection is one of the challenging tasks in autonomous aerial refueling due to the requirement for accuracy and rapidity.Saliency detection based on image intrinsic cues can achieve fast detection,but with poor accuracy.Recent studies reveal that optimization-based methods provide accurate and quick solutions for saliency detection.This paper presents a hybrid pigeon-inspired optimization method,the optimized color opponent,that aims to adjust the weight of color opponent channels to detect the drogue region.It can optimize the weights in the selected aerial refueling scene offline,and the results are applied for drogue detection in the scene.A novel algorithm aggregated by the optimized color opponent and robust background detection is presented to provide better precision and robustness.Experimental results on benchmark datasets and aerial refueling images show that the proposed method successfully extracts the saliency region or drogue and exhibits superior performance against the other saliency detection methods with intrinsic cues.The algorithm designed in this paper is competent for the drogue detection task of autonomous aerial refueling.
基金Acknowledgment This study was supported by the National Natural Science Foundation of China (grant 61101155) and the Jilin Province Science and Technology Development Program (20101504).
文摘This paper presents a biologically inspired local image descriptor that combines color and shape features. Compared with previous descriptors, red-cyan cells associated with L, M, and S cones (L for long, M for medium, and S for short) are used to indicate one of the opponent color channels. Stepping forward from state-of-the-art color feature extraction, we exploit a new approach to compute the color orientation and magnitudes of three opponent color channels, namely, red-green, blue-yellow, and red-cyan, in two-dimensional space. Color orientation is calculated in histograms with magnitude weighting. We linearly concatenate the four-color-opponent-channel histogram and scale-invariant-feamre-transform histogram in the final step. We apply our biologically inspired descriptor to describe the local image feature. Quantitative comparisons with state-of-the-art descriptors demonstrate the significant advantages of maintaining invariance to photometric and geometric changes in image matching, particularly in cases, such as illumination variation and image blurring, where more color contrast information is observed.